Engineering, Mathematics and Physical Sciences

PhD opportunities in Engineering, Mathematics and Physical Sciences  

Thinking about a PhD at Exeter? We have a range of PhD project opportunities available in the College of Engineering, Mathematics and Physical Sciences in the areas of: Computer Science, Engineering, Geology, Mathematics, Mining and Minerals Engineering, Physics and Astronomy and Renewable Energy.

Next steps 

If you are interested in a PhD with us, please search our current research projects below and contact the relevant supervisor (email addresses are included in project details) to express your interest and arrange a discussion.  

The projects below are self-funded and therefore applicants need to find external funding sources to cover tuition fees, living expenses and research costs (bench fees) associated with the project. 

About our research 

We are committed to undertaking research that will help to tackle some of the biggest problems of the 21st century: modelling climate change, sustainable urban water supply, malaria diagnosis, new optical imaging techniques to treat brain disease and bomb-proof materials. Much of the research is interdisciplinary, with academics across the College collaborating to explore topics in more depth. 

The projects below are self-funded and therefore applicants will need to find external funding sources to cover tuition fees, living expenses’ and research costs (bench fees) associated with the project.

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Project Title: A thermal model for cooling and crystallisation of basaltic magma: a case study of the Skaergaard intrusion, Greenland
Project Description: This project aims to generate a new thermal model for the Skaergaard intrusion, and by analogue, extrapolate this knowledge to mid-ocean spreading ridges.

How long does it take magma to crystallise? This simple question is essential to understand the dynamics of the spreading of tectonic plates and the evolution of volcanic terranes. The crystallisation of basaltic magma is exceptionally well described from the Skaergaard intrusion, which underwent extreme differentiation in a closed system. However, the most thermal model was produced in 1976, and is by modern standards extremely basic. Knowledge of magma dynamics, thermodynamics and the processes of compositional differentation has vastly evolved since then, and modern computers allow for 3d models with many million interacting cells. The project will require a student with a strong background in mathematic geology, thermodynamics, and particularly 3d modelling/simulation.

Additional Project costs: N/A

Supervisors:   Professor Jens C Andersen, Camborne School of Mines, Dr Justin Hinshelwood, Renewable Energy
Contact email:   J.C.Andersen@exeter.ac.uk

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Project Title: Extraction for the green energy transition in West Africa
Project Description: West African nations produce industrial minerals, gold and diamonds, and have significant untapped resource potential to supply emerging markets for technology metals. The vulnerability of nations to changes in demand for fossil fuels varies, as a consequence of Net Zero policies in consumer nations. Increased production for modern technology metals in support of regional economic development may be in line with sustainable mining aspirations. “The Africa Mining Vision” calls for policy coherence across mineral resource-rich African countries: it integrates the social, economic, environmental and governance dimensions of local, national and international policies. This project interrogates Social Licence to Operate (SLO) in the context of (i) raw materials production in West Africa for the green energy transition, (ii) translation of responsibility across the green-energy value chain, (iii) the relationship between the formal and informal mining sectors in West Africa, (iv) translation of learning from case studies for critical intervention points and policy coherence. The student will analyse the impacts of resource production, the extent to which SLO is developed, and whether SLO successfully mitigates negative impacts. The project provides a foundation for translation of best practice to limit global outsourcing of social and environmental degradation.

Additional Project costs: N/A

Supervisors:   Kathryn Moore, Penda Diallo
Contact email:   k.moore@exeter.ac.uk

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Project Title: Biominerals in mine wastes: Evaluating the potential for sequestration of toxic elements

Project Description: Mine wastes are unwanted and uneconomic materials (for example, rock, sediment, tailings, metallurgical wastes and dusts) that are found at or near mine sites in almost every country in the world. They often contain elevated concentrations of toxic elements such as antimony, arsenic, cadmium, copper, lead and zinc. The minerals that form in mine wastes can take up and immobilise these toxic elements in their structures, making the elements less bioavailable. The formation of these minerals can be facilitated by microorganisms such as bacteria and fungi. The aims of this project are to determine the mechanisms by which biominerals sequester toxic elements from mine wastes. Biominerals will be collected from mine wastes in Cornwall, UK, which has had a long history (> 2000 years) of mining. They will be characterised using geochemical and mineralogical techniques, and the organisms involved will be determined using microbial analysis. Students will have the opportunity to work in the world-renowned Camborne School of Mines and Environment and Sustainability Institute at the University of Exeter.

Additional Project costs: £20,000

Supervisors:   Professor Karen Hudson-Edwards, Dr Laura Newsome
Contact email:   k.hudson-edwards@exeter.ac.uk

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Project Title: Tungsten in mining-affected environments: Geochemistry, mineralogy and resource potential

Project Description: Tungsten is a rare metal and critical raw material used in used in alloys, permanent magnets, chemical applications and electronics. Historic mining of tungsten has resulted in its enrichment in mine wastes such as tailings and process waters, which in turn can contaminate surface waters and soils, leading to ecosystem toxicity. A better understanding of the geochemical and mineralogical cycling of tungsten in mining wastes will help to design remediation and management schemes, and also to evaluate the potential for extraction of waste tungsten as a secondary resource. The aims of this project are to determine the geochemistry and mineralogy of tungsten in representative mine wastes in Cornwall, UK, which has had a long history (> 2000 years) of mining. The wastes will be characterised using geochemical and mineralogical techniques, including (but not limited to): ICP-MS, ICP-OES, laser ablation ICP-MS, IC, SEM-EDX, QEMSCAN, XRD and XRF. Fieldwork (mine waste sampling campaigns) will also be conducted across a range of beautiful field sites across the SW of England. Students will have the opportunity to work in the world-renowned Camborne School of Mines and Environment and Sustainability Institute at the University of Exeter. We are looking for a highly motivated individual who has a strong background in mineralogy, and ideally, mineral processing.

Additional Project costs: £15,000

Supervisors:   Professor Karen Hudson-Edwards, Dr Rich Crane
Contact email:   k.hudson-edwards@exeter.ac.uk

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Project Title:  Development of hybrid electrochemical systems for the upcycling of acid mine drainage into functional nanoproducts
Project Overview:  
Acid mine drainage (AMD) is an acidic solution created by the oxidation of sulphide minerals, typically associated with areas of legacy metalliferous and coal mining. It is considered to be one of the foremost environmental issues globally, often compared alongside climate change and microplastic pollution in terms of ecological risk. The threat posed by AMD is primarily due to the elevated concentrations of ecotoxic metals (As, Cd, Pb, etc.) but it also contains those which would be economically beneficial to recover (Fe, Cu, Ni, Zn, etc). This PhD project will focus on this area and seek to design novel electrochemical processes (based around hybrid forms of electrowinning) in order to understand how to selectively (and sequentially) recover metals from AMD for a range of different “high value” products and applications (water filtration, catalysis, antiviral activity, etc.).

Additional project costs: approx £10000

Supervisors: 
Dr Rich Crane; Professor Karen Hudson Edwards
Contact email: 
r.crane@exeter.ac.uk

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The projects below are self-funded and therefore applicants will need to find external funding sources to cover tuition fees, living expenses’ and research costs (bench fees) associated with the project.

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roject Title: Cyber-Physical Systems for Safety- or Security-Critical Applications

Project Overview: Cyber-physical systems (CPS) connect the physical world with the internet, i.e., they
usually consist out of physical (analogue system supporting continuous change) parts and cyber (digital systems supporting only discrete change) parts. They are, in the form of intelligent sensors and actors the corner-stone of the Internet of Things (IoT) or Industry 4.0 applications. Ensuring the security and/or correctness of CPS is particularly challenging: the combination of physical and digital aspects create novel attack scenarios (security) and traditional verification techniques only focus on the digital parts of systems.  Concrete PhD topics in this area could, e.g., range from developing formal verification techniques for CPSs to developing (security) testing techniques for CPSs to CPSs specific model-driven security approaches to developing programming models that are can guarantee security by design.

Additional project costs: Applied research £500-£1000

Supervisors:
Professor Achim D. Brucker
Contact email:
a.brucker@exeter.ac.uk

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Project Title: Formal Approaches to Trustworthy Edge/Fog/Cloud-Computations
Project Overview:  Modern computing applications combine a variety of different “computing layers”, from powerful cloud servers, to fog and edge computing, down to IoT devices (smart devices) that have very limited computational power (and that are also limited by other constraints, e.g., power consumption). Each of these different layers provides
different capabilities (both in terms of functional and non-functional aspects) and enforces different limitation (again, both in terms of functional and non-functional aspects). To utilize the available resources efficiently and to be able to move flexible between the different layers, new programming and development models need to be developed that support to transfer computations (algorithms) easily between the different layers.  Concrete PhD topics in this area could, e.g., range from developing formal verification approaches for IoT/Edge/Cloud computing to developing domain specific programming paradigms/languages, to model-driven development approaches.


Additional project costs:
N/A

Supervisors: Professor Achim D. Brucker
Contact email:
a.brucker@exeter.ac.uk

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Project Title: Analysing resistance training using inertial sensors
Project Overview:  This project will focus on how to use wrist-worn inertial sensors, that is, accelerometers and gyroscopes, to classify and analyse exercises for resistance training. The resulting algorithms can be used in smartwatches for fitness tracking. A particular focus will be on classifying movements as rotations or translations, using generalized-likelihood ratio tests. This is very similar to how inertial sensors are used to detect zero-velocity instances in foot-mounted inertial navigation. The results of these classifications can then be used to make a more fine-grained exercise classification by analysing the direction of these movements. In addition, we will use machine learning to estimate other quantities, such as form and the weight being used. For example, we may first record data from multiple experienced personal trainers when doing exercises with proper form. We could then assess the similarity between these executions and those of less experienced individuals when doing the same exercises, and thereby get an assessment of their technique. Ideally, we would like to analyse their form in such a way that we can provide detailed feedback on how they should change their movement to achieve proper form, only based on the inertial data.

Additional project costs: N/A

Supervisors: Dr Johan Wahlström
Contact email: 
j.wahlstrom@exeter.ac.uk

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Project Title:  Formal Approaches to Web/Browser Security
Project Overview:  Today, web applications “running” in a web browser cover nearly all aspects of our life. This also includes applications in safety, security, and privacy critical areas. Thus, web browsers should be developed as rigidly and formally as operating systems.  While formal methods are a well-established technique in the development of op-
erating systems, there are few proposals for improving the development of web browsers using formal approaches. And even if important aspects (due to dynamic nature of web technologies, it is unlikely that a full formal verification can be achieved with reasonable efforts), such as the Document Object Model (DOM) or the Content Security Policy (CSP) of a web browser are formalized and properties are formally verified, it is still unclear how this related to the actual implementations running on various operating systems and hardware architectures.  Concrete, PhD topics in this area could, e.g., range from formalizing and verifying aspects of the security model of web browsers and/or web applications to applying specification-based testing approaches for testing and evaluating browser security APIs to developing an approach for generating run-time monitoring solutions for web applications and/or browsers from formal models.


Additional project costs: N/A

Supervisors:
Professor Achim D. Brucker
Contact email:
a.brucker@exeter.ac.uk

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Project Title:  Security Testing and/or Reverse Engineering
Project Overview:  Traditionally,security testing is divided into static approaches (i.e., approaches that analyze the source code, byte code, or binaries without executing them) and dynamic approaches. Both approaches are well understood to have different advantages and disadvantages. To improve the precision and coverage of security testing tools (and to increase the degree of automation and speed in secure software development), innovative security testing approaches need to be developed. For example, promising approaches bringing security testing to the next level combine static and dynamic aspects, integration of machine learning to security testing, or combining security testing with formal verification.  Concrete PhD topics in this are should work on improving the state of the art in security testing, e.g., improving its applicability in modern software development processes, improving its precision, increasing its degree of automation, or developing testing approaches for detecting novel attack vectors. These topics can be addresses using formal methods, applied approaches (e.g., search-based testing, machine learning) or empirical studies for developing a better understanding of the applicability of existing approaches.


Additional project costs:
Applied research £500-£1000

Supervisors: 
Professor Achim D. Brucker
Contact email: 
a.brucker@exeter.ac.uk

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Project Title:   Magnetic positioning for social distance monitoring
Project Overview:  This project will focus on implementing magnetometer-based positioning algorithms for the purpose of enforcing social distance monitoring requirements in a pandemic environment. Despite the introduction of vaccines to COVID-19 at the end of 2020, we can still expect social distance recommendations to remain for a foreseeable future in many contexts. There are, for example, many services that need to be up and running, such as hospitals, and in addition, we may see more people going back to work after having worked from home for a long period of time. One way to make the compliance to social distancing requirements easier is to make use of modern positioning technology. Since infrastructure-based positioning solutions are still too expensive to be installed on a large scale, a feasible alternative could be to make use of smartphone-embedded magnetometers. Here, one alternative could be to estimate position based on local, spatial variations in the geomagnetic field. While this technology has been studied for many years, the difficulty with smartphone-based solutions is that they have to account for the changing orientation of the smartphone. In addition to geomagnetic positioning, we will also consider positioning using magnetometer arrays and an induced magnetic field.

Additional project costs:  N/A

Supervisors: Dr Johan Wahlström
Contact email:
 j.wahlstrom@exeter.ac.uk

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Project Title:  Securing the Software Supply Chain
Project Overview:  Today nearly any software being developed relies heavily on third-party components (e.g., Open Source Components). When such components are used with the development of an application, i.e., as part of the software supply chain, the developer of the application using the third-party components becomes responsible for
any security vulnerabilities that the third party component might have. Thus, techniques for detecting and minimizing the risk caused by using third-party components need to be an integral part of any modern secure software development process.  Concrete PhD topics in this area range from analyzing existing vulnerabilities to mining software repositories for hidden fixes to generating exploits for known vulnerabilities to evaluate their impact of a consuming application to analyzing which third party components are used to deriving automated fixes or other means of protecting the consuming application.


Additional project costs:
Applied research £500-£1000

Supervisors:
Professor Achim D. Brucker
Contact email: 
a.brucker@exeter.ac.uk

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Project Title:  Virtual reality meets foot-mounted inertial navigation
Project Overview:  Within virtual reality, the motion of a headset, and possibly also other body parts, such as hands, are tracked using some navigation sensors. In low-cost virtual reality systems, only rotations are tracked, but not the absolute position. Thus, the user may experience the virtual world responding as expected when tilting his head, or when looking to the left or right. However, when the user changes position, the virtual world will not move with him. High-end virtual reality systems offer not only rotational tracking, but also positional tracking. The position estimates can be based on, for example, infrared tracking. Unfortunately, these systems tend to be significantly more expensive, and also require additional infrastructure that is external to the VR accessories. In this project, we will explore how to utilize foot-mounted inertial navigation to provide positional tracking for VR systems. Foot-mounted inertial navigation is a low-cost technology that provides long-term stable position estimates by exploiting the foot’s stationarity. We will then look at how to utilize these estimates to also track headset positions, and thereby enable low-cost virtual reality headsets with positional tracking.

Additional project costs: N/A

Supervisors:  Dr Johan Wahlström
Contact email: 
j.wahlstrom@exeter.ac.uk

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Project Title:  Theorem prover-based (Software) Testing
Project Overview:  Theorem prover-based testing combines verification and testing techniques within
a uniform (theorem proving) environment. As such, it allows to seamlessly move between verifying and testing of system properties, allowing to choose the method that is most suitable for, e.g., parts of a system or for certain properties. Theorem prover-based testing combines the advantages of verification (e.g., a high correctness guarantee) with the advantages of testing (e.g., validating an actual system in its actual environment). It has, e.g., been successfully applied to testing security policies of network middle-boxes in general and firewalls in particular, to complex and dynamic access control models and to testing separation aspects of a real-time operating system kernel.  Concrete PhD topics in this area range from extending the theoretical foundations and tooling for theorem prover-based testing to adapting theorem-prover to new application domains.

Additional project costs:  £1500

Supervisors:
Professor Achim D. Brucker
Contact email: 
a.brucker@exeter.ac.uk

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Project Title: Verification or Testing of Security or Correctness Properties for Non-Standard Computing Architectures (e.g. Quantum Computing, FPGAs, GGPUs)
Project Overview:  New emerging computing architectures are currently emerging. This includes moderate changes, such as software-defined-X, where hardware is implemented in software or, the other way round, software that is implemented dynamically in hardware (e.g., using FPGAs) as well as radical new approaches to computing such as quantum computing or DNA computing. All these approaches have in common that traditional programming, verification,and testing approaches are not necessarily suitable for ensuring the security, safety, and/or correctness of systems based on non-standard computing architectures. At the same time, it is unclear to what extent traditional verification and/or testing approaches could benefit from using non-standard computing architectures.  Concrete PhD topics in this area could develop novel programming, testing, or verification approaches for non-standard computing architectures, analyze the security/privacy aspects of non-standard computing architectures, or investigate their application to traditional verification or testing approaches.

Additional project costs: Applied research costs £1500

Supervisors:
Professor Achim D. Brucker
Contact email: 
a.brucker@exeter.ac.uk

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Project Title: Mixed integer multi-modal optimisation using evolutionary computation
Project Overview:  In multi-modal optimisation, we seek not simply to discover a single design x which (without loss of generality) maximises f(x) given any constraints, but all x∗ ∈ X which obtain the maximum possible function response (or within some epsilon of it), but which inhabit isolated peak regions in the objective function. That is, the mapped objective values in the immediate region of an x∗ are all equal or lower than f(x∗).

There are many reasons that the problem owner may wish multiple mode solutions to be discovered rather than a single 'best' solution. By discovering a range of different designs, which are operationally equivalent, insight into the problem domain may be extracted. Also, it may transpire that some designs are not machinable – i.e., X is mis-specified, and therefore a range of solutions mitigates against this. Finally f() may be in error in certain regions, therefore a wide range of good solutions can be helpful if the 'best' design does not perform as emulated.

This project will develop heuristic optimisation techniques for the under-explored area of multi-modal mixed-integer problems: most work on multi-modal algorithms has been directed toward continuous or combinatorial spaces, however mixed integer spaces occur regularly in practice.

Additional project costs:  N/A

Supervisors:  Prof Jonathan Fieldsend
Contact email: 
J.E.Fieldsend@exeter.ac.uk

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Project Title:  Integrating Formal and Semi-Formal Aspects of System Development for Certification Processes
Project Overview:  Many certification processes for safety-critical or security-critical applications (e.g., autonomous vehicles, smart cards) require the combination of rigid (e.g., formal specifications and formal verification) development steps with informal aspects. Concrete PhD topics in this area could focus on developing formal methods support for safety or security standards (e.g., by extending a tool developed in our group,
called Isabelle/DOF) that allow strong links between the formal and informal/semi-formal aspects of system development. Moreover, PhD topics in this area could, e.g., develop (semi-) formal support for safety or security certification processes or develop verification or testing approaches that are optimized for certification processes.

Additional project costs: Optional research visit costs£1500

Supervisors:
Professor Achim D. Brucker
Contact email: 
a.brucker@exeter.ac.uk

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Project Title:  Formal Approaches to Security and Privacy
Project Overview:  Security and privacy are properties that are notoriously difficult to achieve. Formal and semi-formal methods, i.e., approaches based on mathematics or logic can help to detect security and privacy issues as well as support the development of systems that are secure-by-design or follow a privacy-by-design approach.  We are working on several problems in this area, ranging from novel approaches of verifying security protocols, formally analyzing the privacy of systems, or developing testing approaches that integrate well with verification approaches.  Concrete PhD topics in this area could focus on formal approaches for testing or verifying the security or privacy of systems, or security (e.g., verification of security protocols, formal verification/analysis of privacy enhancing technologies, or working formal privacy analysis approaches such as alpha-beta-privacy).

Additional project costs: Optional research visit costs £1500

Supervisors:
Professor Achim D. Brucker
Contact email: 
a.brucker@exeter.ac.uk

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Project Title:  Trustworthy ML/AI for High-Assurance Systems
Project Overview:  An increasing number of safety-critical or security-critical application is being based on machine learning (ML) or, more general, artificial intelligence (AI), methods. Compared to traditional software development, the behavior of such systems is not designed by a human and laid down in a computer program. Instead, systems are
trained using some form of learning and the trained system (often called model) are  then used “in production”.  The lack of a human understandable computer program that describes the behavior of the system in all possible situations, makes it hard to analyze and understand the possible behavior of ML/AI-based systems in corner cases. This is particular worrisome in safety critical applications (where systems might enter such “corner cases’ accidentally), where wrong decisions might endanger the life of humans as well as in security critical application (where an attacker might actively try to force the system in a “corner case”) where the security or privacy of systems or data might be harmed.  Concrete, PhD topics in this area could develop new verification or testing approaches that help us to understand (trained) ML/AI-based systems or that even can show that a system always operates within certain boundaries (e.g., safety margins).  Another area of PhD topics is the development of verification and testing methods for learning algorithms or the development of learning approaches that can ensure that AI/ML models stay within certain safety boundaries.

Additional project costs:
Optional research visit costs £1500

Supervisors: 
Professor Achim D. Brucker
Contact email: 
a.brucker@exeter.ac.uk

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Project Title: Mobile data collection on movement and muscular activity using EMG and inertial sensors
Project Overview:  Electromyography is the most common technology for assessing muscular activity during specific physical exercises, conducted for the purpose of, for example, hypertrophy or rehabilitation. However, electromyography itself does not provide any information about how specific exercises are performed. In laboratory environments, the electromyography signals can be combined with data from motion capture systems, which provide accurate, high-resolution data on human movements. However, movement patterns over the course of a day or outside of a laboratory environment may be very different. Therefore, in this project, we will focus on how to fuse inertial and electromyography signals to obtain a mobile data collection system that can extract rich information on physical exercises. In particular, we will focus on how muscular activity (measured using electromyography) changes with the form of the user (measured using inertial sensors). In addition, we will consider rehabilitation settings which benefit from remote activity and muscle monitoring over long periods of time.

Additional project costs:  N/A

Supervisors: Dr Johan Wahlström
Contact email:
 j.wahlstrom@exeter.ac.uk

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Project Title:  Secure/Safe Patching of IoT/Sensor Networks or Smart Devices
Project Overview:  Our modern life depends heavily on smart devices that are often widely deployed and that have a long life expectancy, e.g., used in autonomous vehicles, smart home appliances, IoT sensors and actors in Industry 4.0 applications. Often these devices are security and/or safety critical and, e.g., due to the large deployments in complex environments, hard to upgrade. Thus, novel techniques for upgrading and/or patching smart devices over their full life-time need to be developed to ensure the safe and secure operation of smart devices is from outermost importance.  Concrete PhD topics in this area could, e.g., range from formally verifying upgrade/patching approaches, to smart device-specific approaches to distributing and/or applying patches to developing easy to upgrade and maintain smart devices.

Additional project costs: Applied research costs £1,000

Supervisors: 
Professor Achim D. Brucker
Contact email:  
a.brucker@exeter.ac.uk

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Project Title: Deep learning for inertial sensor arrays
Project Overview:  The idea of inertial arrays is to place a large number of inertial sensors on one array. Inertial arrays do not only provide more accurate estimates than conventional sensor units, but can also do things that conventional sensor units cannot do at all. For example, inertial sensor arrays can circumvent limitations in the dynamic range of conventional sensor units, and can estimate angular acceleration based on readings from spatially distributed accelerometers. One of the factors that is holding back further development in inertial sensor arrays is the large number of systematic sensor errors that effect the sensor measurements, particularly during high dynamics. In addition, the measurements depend on the exact positions of the sensor elements, which cannot be measured manually. In this project, we will investigate the use of deep learning for estimating navigation quantities using inertial sensor arrays. In this way, we will circumvent problems related to systematic sensor errors and unknown sensor positions. The training data will be collected from motion capture systems.

Additional project costs: N/A

Supervisors: Dr Johan Wahlström
Contact email: 
j.wahlstrom@exeter.ac.uk

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Project Title:   Networked narratives, framing and culture wars
Project Overview:  Narratives are the stories we tell about the world. They are the way we connect new information to preexisting beliefs and opinions. For instance, two people might read the same news article about their government, and one might say the article shows how their government is incompetent, while the other might say the article is biased, and their government is doing a fantastic job. Both might interpret the article differently, each reinforcing different combinations of beliefs and opinions they might hold – and ultimately, different sets of narratives – about the world.

This project will develop and apply tools from machine learning, natural language processing, and social network analysis to study the networks of narratives around particular political topics, put together by politicians and other influential figures. Data is available through public archives from parliaments and social media.

Possible questions include seeing how different politicians/parties frame the same topics (e.g. COVID-19, vaccines, misinformation) in different ways, or which stances (pro-this, against-that) are expressed together, or even identifying networked narratives by tracking similar stories told in the same time span. In this way, this project should contribute to the fields of data science, computational social science and political communication."

Additional project costs:  N/A

Supervisors:  Dr Chico Camargo
Contact email: 
f.camargo@exeter.ac.uk

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Project Title:   Distributed Real Time Machine Learning for UAV Swarms
Project Overview:  Machine learning for swarms of UAV (Unmanned Aerial Vehicles) could empower them to complete more sophisticated tasks, such as surveying, agriculture, and defense. For example in agriculture, the application of a swarm of dozens of UAVs flying over a paddock simultaneously has potential to yield useful and timely information about vegetation biomass, the presence of parasites, and other agricultural attributes.

This project will develop state of the art distributed machine learning techniques for such settings, taking into account swarm dynamics, data fusion characteristics, communication delay, and information capacity. The result will include practical algorithms for distributed real time machine learning, with empirical evaluation of optimal hyper-parameters suitable for current state of the art UAV swarms. Trade offs of accuracy, latency, energy usage, memory consumption, and redundancy will also be quantified.

Additional project costs:
N/A

Supervisors: Chunbo Luo; Yoni Nazarathy (The University of Queensland, Australia)
Contact email: 
c.luo@exeter.ac.uk

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Project Title:   Modelling urban environments using new forms of data
Project Overview:  Recent years have witnessed an increased urbanisation of the environment we live in, with rapidly growing cities and swift societal changes. Traditional techniques for studying urban environments are often either too costly or too slow in order to be used by policy makers and governments.
However, recent advances in computational methods and the sudden availability of large amounts of data on our cities and behaviour has opened up unprecedented opportunities for studying urban environments at scale, and our behaviour within them. This project will focus on studying human behaviour at the collective and individual level in urban environments using a variety of data sources, such as mobile phone data, OpenStreetMap data and social media.

Additional project costs:
N/A

Supervisors: Dr Federico Botta
Contact email: 
f.botta@exeter.ac.uk

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Project Title:  AI Safety and Robustness
Project Overview:  This project aims to explore possible solutions for assuring the robustness and safety of AI models, especially deep learning. You are allowed to choose any specific topic related to AI Safety and Robustness. As a first step, you can look at the survey paper “A survey of safety and trustworthiness of deep neural networks: Verification, testing, adversarial attack and defence, and interpretability”, where you can get a sense of which specific aspect/topic you are interested in. You are welcome to contact me to have a discussion before you start your PhD proposal.

Additional project costs:
N/A

Supervisors:   Dr Wenjie Ruan
Contact email:  
w.ruan@exeter.ac.uk

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Project Title: Trustworthy AI for Industrial Internet of Things

Project Description: The Industrial Internet of Things (IIoT) has been widely adopted to facilitate the digital transformation of traditional industries towards Industry 4.0. Massive IIoT data will be collected and analysed for intelligent decision making to ensure the security, resilience and safety of industries. AI and machine learning models have been widely used for effective and efficient data analysis. However, these models may make bias and unfairness decisions which may eventually harm humans and cause economic losses. This project will develop trustworthy AI and machine learning models that can make responsive decisions for IIoT tasks. Experiments will be conducted to validate the effectiveness of the proposed solutions. The project will also collaborate with industry partners to develop applications and case studies based on the proposed trustworthy models.

Additional Project costs: N/A

Supervisors:   Yulei Wu
Contact email:   y.l.wu@exeter.ac.uk

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Project Title: Future action anticipation using causal discovery

Project Description: The goal of this project is to anticipate the future in a video. To this end, we aim to discover the dependency structure modelling the environment and objects, and how/to what strength they are interacting. This leads to the structural (causal) model which is shown to have a causal effect on how the dynamic system behaves and therefore, the causal model will contribute to our original goal of predicting the future. It can be particularly useful in cases where actions or objects are hard to be detected and they are identified by discovering the causal effects.

Additional Project costs: N/A

Supervisors:   Dr Sareh Rowlands
Contact email:   s.rowlands@exeter.ac.uk

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Project Title: Action recognition in untrimmed videos

Project Description: The goal of this project is to develop an algorithm for automatically recognising a large number of action categories from videos. An action can be either a simple atomic movement performed by a single person or a complex scenario involving multiple people. The algorithm should recognise human actions from videos in a realistic setting. Videos of a given action class could involve different backgrounds, different actors, and be captured from different camera viewpoints. This project addresses the task of recognising human activities in temporally untrimmed videos, where the action of interest may occur at any time in the video.

Additional Project costs: N/A

Supervisors:   Dr Sareh Rowlands
Contact email:   s.rowlands@exeter.ac.uk

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The projects below are self-funded and therefore applicants will need to find external funding sources to cover tuition fees, living expenses’ and research costs (bench fees) associated with the project. 

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Project Title: Advanced Sensors for Atmospheric Pollutants using the Coupling of Light and Sound
Project Overview: There is a rapidly growing demand for cost-effective, portable gas sensors to help improve air quality and reduce emissions. Many important atmospheric pollutants, such as CO and NO, have their strongest characteristic absorption in the infrared region of the spectrum, and the absorption of infrared light forms the basis of many current gas sensors. However, in an infrared gas sensor the signal relating to the presence of a gas is due to a small decrease in a large background signal, limiting the sensitivity of the sensor.
In this project, we will aim to explore an exciting new approach for gas sensing where we use a type of microscopic elastic wave, propagating on the surface of a solid, to detect the sound emitted by a gas molecule when it is illuminated by infrared light. In this case, there is no signal without the presence of a gas. We will explore the fascinating interaction between light, sound and elastic waves, which has the potential to open up exciting new ways of sensing chemical and gases. This highly interdisciplinary project will draw on aspects of physics and chemistry, and will involve theory, simulations, device fabrication and characterisation.
Additional project costs:
£10,000

Supervisors:
Professor Geoff Nash and Professor Francesca Palombo
Contact email:
g.r.nash@exeter.ac.uk

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Project Title: High aspect ratio wings in fully electric aviation industry: dynamic testing and optimisation
Project Overview:  The performance of an aircraft dependents primarily on its wing design. Very flexible wings come from the need for aviation solutions that provide lower fuel consumption, directly reducing emissions and operating costs. A way to achieve highly efficient wings is to consider lighter wing boxes using advanced (and stronger) materials along with longer wing structures; these so-called high aspect ratio wings produce the required lift and desired lower drag forces. However, they are very flexible and therefore, their interaction with the air becomes more complex as the wing behaves largely non-linearly. As a result, several design tools currently used in industry are not fit for purpose anymore.  The PhD project will be an in-depth study of the engineering challenges of using high aspect ratio wings in a future pure electric commercial aviation. In particular the PhD research will primarily aim to develop an accurate experimental procedure to extend the capability of current Ground Vibration Testing to characterised aircrafts with very flexible wings. GVT involves conducting a series of experimental tests to identify the best wing mathematical model. This project involves the use of data-driven (AI) approaches and advanced vibration testing procedures to supports the development of future efficient wings.
Additional project costs: N/A

Supervisors: Dr. Julian M Londono Monsalve
Contact email: J.Londono-Monsalve@exeter.ac.uk

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Project Title: Advanced composites for boosting resilience of strategic equipment operating in wobbling environments in the medical and aerospace industry
Project Overview:  This project aims to study theoretically and validate experimentally the dynamic behaviour of a few layer graphene-rubber composite. The unprecedented combination of mechanical properties achieved by utilising the outstanding tensile strength of graphene to reinforce natural rubber has produced a strong but flexible composite able to dissipate vibration energy. The outcome of this project will be a proof-of-concept lightweight vibration isolator tailored for isolating from vibration sources highly sensitive equipment in the medical and aerospace industry.
The presence of a large number of vibration sources in hospital floors at various frequencies (e.g. pumps, vehicles and pedestrian dynamic loads) is a continuous threat to the effective operation of highly sensitive medical equipment(e.g. microscopes, X-ray and MRI machines). Comparable vibration environments in the aerospace/defence industry could compromise the operation of precision lasers, scanners, control units, antennas and electronic circuit boards operating in mission-critical situations. These vibrations can be transmitted to other devices; for instance, they can have severe adverse consequences on patients under medical treatments or compromise the successful completion of missions when prolonged or excessive vibration interfere with equipment performance. Vibration insulation is therefore essential to ensure the functioning of those highly sensitive machineries.
Additional project costs: N/A

Supervisors: Dr Julian Londono; Prof Maria Rosaria Marsico
Contact email: m.r.marsico@exeter.ac.uk

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Project Title: Engineering Optimisation through Machine Learning and Computational Fluid Dynamics
Project Overview:  Cars, aircraft, trains, wind turbines ... so many engineered objects interact with the air or water around them. Computational Fluid Dynamics (CFD) is the use of computers to solve the governing equations of fluid mechanics and can be used to predict the behaviour of these to a high degree of accuracy; in many industries, CFD is a key tool in the development of better devices and systems. Increasing computer power makes it possible to use CFD to perform automated engineering optimisation, and here in Exeter we are at the forefront of developing Machine Learning tools such as Bayesian Optimisation for this purpose. In this method an automated algorithm evaluates new designs through CFD and iteratively "learns" the best design for the job. By factoring in the results from earlier evaluations, the Bayesian method acts to reduce the number of (expensive) CFD evaluations necessary to do this. (See our paper "Application of multi‑objective Bayesian shape optimisation to a sharp‑heeled Kaplan draft tube", Daniels et al, Optimization and Engineering (2021) https://doi.org/10.1007/s11081-021-09602-6). The aim of the proposed project will be to apply this cutting edge technique to a range of vehicle optimisation problems including cars and trains, and to improve the methodology further, including using Cloud Computing to perform the CFD.
Additional project costs: TBC

Supervisors: Prof Gavin Tabor, Prof Jonathan Fieldsend
Contact email: g.r.tabor@ex.ac.uk

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Project Title: Digital Supply Chain Management for designing a resilient sustainable logistics network design under disruption and uncertainty
Project Overview: 
This project will focus on designing a robust model for sustainable resilient supply chain networks by integrating digital technologies to minimise systematic risks, which can disrupt operations within the supply chain network. Systematic risks can be defined as risks that relate to environmental factors, which are unavoidable, e.g., demand-side uncertainty, supply-side disruption, regulatory, legal, and bureaucratic changes, the occurrence of major natural events (i.e. fires, earthquakes, floods, disease outbreak, etc.) and infrastructure disruption.
Digital technology methodology (i.e., IoT, machine learning, etc.) will be adopted to design this smart supply chain to predict, provide real-time monitoring and solutions when the existing supply chain networks encounter disruptions. Artificial intelligent-based algorithms will be put forward to provide decision support systems to deal with these logistical issues within Industry 4.0 environment.

Additional project costs: N/A

Supervisors: 
Dr Martino Luis
Contact email:
m.luis@exeter.ac.uk

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Project Title: A New Paradigm on Cartilage Repair and Regeneration: Tailored Functionality from its Ultrastructure
Project Overview:  
This project is to establish, evaluate and optimise a novel scaffold-free framework in cartilage repair in the context of ageing and also osteoarthritis (OA), one of the most common musculoskeletal disorders. The approach of this project will allow the regenerated tissues to mimic the nanostructure and functionality of the nature cartilage as a biomimetic template, and the outcome will provide an assessment of its potential in clinical applications. The scope and impact of this project are well-aligned with the UK research priorities on Biomedical Physics, Bioengineering and Biosciences. This work will impact more than 9 million people in the UK suffering from compromised cartilage functionality and costing the health service more than £4 billion per year. More importantly, the knowledge and the approaches from this proposal are expected to facilitate the development and evaluation of new OA drug candidates, and the methods being developed for analysing tissue mechanics at a molecular scale are directly applicable to a broad range of soft tissues beyond cartilage for future research.

Additional project costs: £6500

Supervisors: 
Dr Junning Chen (Engineering), Dr Ben Sherlock (Medicine), Prof. Peter Winlove (Biophysics)
Contact email: 
j.chen3@exeter.ac.uk

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Project Title:   Novel energy harvesting devices or circuits for powering wireless sensor systems
Project Overview: 
Most of today’s wireless sensor nodes in networks (WSNs) are powered by batteries. The batteries, as the power source, having a very limited capacity, need to be regularly replaced once they are depleted to allow nodes to continue operating. It has been recognised that the roll-out of more wide-spread and large-scale nodes in WSNs will be severely limited by the power supply. How to power the rapidly growing number of nodes in WSNs sustainably without using batteries is a significant research topic for the WSN applications in the 21st Century.

One powerful means to solve the problem is to develop energy harvesting technologies, which capture energy from its surrounding structure and environment via a harvester, and convert and store it into usable electric power via a power management circuit. The energy harvesting technologies are therefore capable of achieving self-powered wireless sensor systems, operating for years without the need for batteries or mains power, eradicating concerns related to energy deterioration in system operations, reducing maintenance costs, including the time and workforce required to replace batteries, and satisfying the industry's requirement for fit-and-forget asset monitoring systems.

The PhD students will research one or two topic listed below for their study at the Energy Harvesting Research Group at the University of Exeter. The PhD students will develop novel energy harvesting method, and/or efficient power management and/or low power wireless sensor systems for energy harvesting powered wireless sensor system applications.

Topic 1 is to research a novel energy harvesting structure to convert mechanical vibration into electrical energy via mechanical design.
Topic 2 is to research efficient electronic circuits to convert harvested energy into usable electric power for energy harvesting technologies via circuit design research.
Topic 3 is to research low power context-aware and/or energy-aware wireless sensor systems, able for nodes to adapt to energy harvesting technologies via hardware and software research.

Additional project costs: £11000 p.a

Supervisors: 
Prof Meiling Zhu, Dr Zheng Jun Chew, Tingwen Ruan
Contact email:
m.zhu@exeter.ac.uk

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Project Title:  3D Porous Ceramics Nanostructures as Support for Advanced Applications
Project Overview: 
The main aim of the project is to create porous 3D ceramic nanostructures then explore their applications in a number of advanced areas, including catalysts, sensors, EM shielding etc. Ceramics offer irreplaceable advantages over other types of materials, such as their chemical inertness, thermal stability, high Young's modulus, stability, etc. Via materials synthesis control, we hope to obtain 3D porous ceramic nanostructures that offering a diverse structural features to suit for specific applications in these areas.

Nanomaterials synthesis, advanced materials characterisation and specific materials property assessment skills will be developed in this project.

Additional project costs: £6000

Supervisors: 
Prof Yanqiu ZHU, Dr Yongde Xia
Contact email: 
Y.zhu@exeter.ac.uk

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Project Title:  Advanced nanocomposites for efficient mechanical energy harvesting
Project Overview: 
This project is designed based on linking advanced materials science, energy harvesting and wearable technologies together.

When two insulating materials with different electron affinities get into contact, an accumulation of charges at their surfaces can be observed. The challenge is how we can explore such contact electrification phenomenon and effectively harvest the mechanical energy. Polyvinylidene fluoride (PVDF), with its high electronegativity, has a huge potential for triboelectric nanogenerators, and the output of such energy harvesting devices can further be enhanced when nanomaterials (e.g. carbon nanotubes) are used as fillers. This multidisciplinary project aims at developing new nanocomposites by exploring different combination of triboelectric materials, to evaluate their mechanical energy harvesting potentials. Skills from the preparation of nanocomposites to characterisations of their microscopic and morphologic features, to their triboelectric performance will be thoroughly trained during this project. Besides the PVDF nanocomposites, these triboelectric materials include textile substrates, which combined with an appropriate flexible electrode material (e.g. graphene) can open the way to a full integration of these energy harvesting devices with wearable technologies.

Additional project costs: £6000

Supervisors: 
Prof Yanqiu ZHU and Dr Ana Neves
Contact email: 
Y.zhu@exeter.ac.uk

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Project Title: Intelligent Microtome for Processing of Difficult-to-cut Tissue with the Assistance of Machine Learning
Project Overview:  
Modern-day histology of biological tissues requires precision cutting of a wide variety of tissue samples for histological analyses. Lots of common problems can be identified at the conventional microtome sectioning including creation of curling sections and sections stick to the blade, which made high-quality sections hard to obtain. In addition, creating great sections using a conventional microtome takes a great deal of skill and experience. Histologists have to take a long-time training to be qualified via the trial and error learning. Therefore, an intelligent automatic microtome is strongly required for sectioning biological tissues. The novel microtome could make the labour intensive job efficient and effective with the assistance of machine learning.

Additional project costs: £2000

Supervisors: 
Dr. Dong WANG
Contact email: 
d.wang2@exeter.ac.uk

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Project Title:  Self-powered wearable sensors
Project Overview:  
Electronics devices fully integrated with textiles are at the forefront of wearable technology. However, any e-textile devices require a power supply, which is not always as wearable as the technology it sustains. Harvesting energy from the human movement offers an integrated solution to power wearable devices. Two insulating materials rubbing together (e.g. fabrics) can create an accumulation of electric charges as their surface when their electron affinity is sufficiently different, in what is commonly known as static electricity. A careful choice of triboelectric materials, along with appropriate electrodes to collect those charges, can produce enough power to operate electronic components. This multidisciplinary project aims at exploring these triboelectric nanogenerators as wearable mechanical energy devices, with materials and nanotechnology optimisation approaches. Such devices have the potential to be used in shoe soles and insoles, as well as around joints and moving body parts. For this, graphene electrodes will be used due to their demonstrated flexibility, inertness, and compatibility with textiles. The electrical signal that those materials generate when in motion can also be used for sensing purposes, allowing the monitorisation of exercise or physiotherapy, for example, highlighting the potential of this technology in the field of remote healthcare.

Additional project costs:  £5000

Supervisors: 
Dr Ana Neves, Prof Monica Craciun
Contact email:  
a.neves@exeter.ac.uk

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Project Title: Data Analytics for Smart Management of Pipe Networks
Project Overview: 
Climate and global changes and asset deterioration are putting great pressure on water systems. The water industry has made a good progress in responding to these challenges, environmental commitments, customer expectation and regulatory requirements. However, still more needs to be done on topics that affect majority of utilities in developed and developing countries. Internet of things and big data technologies have progressed a lot in recent years. The sensors create big data, and by applying appropriate data analytics to them, valuable information could be obtained and used in asset management. Smart and intelligent water systems will be more connected and operated with more data in real time to achieve maximum efficiency and effectiveness.
This project aims to use monitoring data to improve asset management of urban water networks. This will involve:
- Assessment of suitability of the existing monitoring system and identifying optimum new monitoring system that would deliver maximum benefit to the decision making process.
- Development of novel data analytics to extract information from time series data collected by smart sensors.
- Development of optimum asset management intervention options to improve water system’s performance and resilience to short-term shocks and long term stresses.

Additional project costs:  N/A

Supervisors: 
Prof Raziyeh Farmani
Contact email:  
r.farmani@exeter.ac.uk

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Project Title: Transient Stability in a BESS-integrated Power System by High-frequency Modelling Technique
Project Description: Battery Energy Storage System (BESS) is an important tool to improve the Smart Grid’s reliability and efficiency, especially given the UK future energy scenario of increasing system demands and massively growing renewable energy integrations. The fast response and the ability of the bidirectional power flow control provide the BESS high flexibility and cost-effectiveness, but also bring challenges to the network transient stability. This project will investigate the dynamic performances of a power system when a grid-scale BESS is integrated by a novel connection approach, i.e., through power transformers. The student will combine the knowledge of power electronics, control theory, power transformer and power system analysis with simulation skills and develop an accurate high-frequency BESS-integrated network model, by which transient issues such as transformer non-linearity, transformer energisation inrush currents and system harmonic resonance will be studied. The interaction mechanism between the transformer frequency response and BESS transient outputs will be investigated. The goal of this project is to identify issues with system transient stability and seek mitigation measures, and further improve the applicability of the BESS.

Additional Project costs: N/A
Supervisors: Prof. Zhongdong Wang (1st), Dr. Shuhang Shen (2nd)
Contact email: Zhongdong.wang@exeter.ac.uk; s.shen@exeter.ac.uk

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Project Title: Transient Stability and Integration of Power Flow Controllers into Six-phase Transmission Technology to Unlock the UK Transmission Boundary Capability

Project Description: To achieve the UK net-zero target in 2050, the GB network is under a fast transition to clean energy dominated by intermittent renewables. In addition, the projected UK electricity demand in the coming decades is facing extensive growth. The power transfer capability of existing transmission lines needs to be uprated. Six-phase technology is a feasible approach to almost double the transmission capability because a six-phase line can operate at line voltage that is the same as the line-to-neutral voltage. This project will investigate the impacts on a meshed power grid when the main double-circuit three-phase transmission corridors are operated in six-phase. The main focus is transient analyses under various short-circuit fault conditions and the design of an appropriate protection scheme. To line up with the large amount of renewable energy generation, how the six-phase technology can cooperate with power flow controllers to maximise the power transfer stability and controllability will also be studied. The student will need power system knowledge and skills in the use of transient simulators. The goal of this project is to gain a deep understanding of the limits of the six-phase transmission technology and the advantages of adapting three-phase double-circuit lines into six-phase lines.

Additional Project costs: N/A

Supervisors:  Prof. Zhongdong Wang (1st), Dr. Shuhang Shen (2nd)
Contact email:   Zhongdong.wang@exeter.ac.uk; s.shen@exeter.ac.uk

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Project Title: Bio inspired flight control
Project Description: This research will investigate nature inspired flight control of a small unmanned aerial vehicle (UAV). In recent years, there has been an increase of interest to draw inspiration from nature for an efficient flight of small UAV. This includes flapping wings, morphing wing, perching and dynamic soaring. At the same time, there has been an increase in research in the area of reconfigurable flight control, which includes fault tolerant control.

The idea is to investigate the combination of reconfigurable control and exploit the available control on a highly actuated small UAV inspired by nature. As a starting point, the problem of dynamic soaring of highly efficient flight Albatross (large sea bird) will be considered. An appropriate UAV configuration inspired by the study of the anatomy of the Albatross will be investigated. Then, other nature-inspired bird configuration such as ‘gull wing’ position will also be considered.

It is envisaged that this project will consist of mathematical model development of an Albatross using computational fluid dynamics (CFD) software (to generate the aerodynamic database) and MATLAB/SIMULINK to model the dynamic motion of the UAV. This will allow novel reconfigurable control schemes to be developed and tested on the model.

Additional Project costs: N/A

Supervisors:   Dr Halim Alwi
Contact email:   h.alwi@exeter.ac.uk

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Project Title: Modelling, Simulation and Control System Design of flapping wing UAVs
Project Description: Academic research in the area of Unmanned Aerial Vehicles (UAVs) has received significant attention in the last few decades. This is driven by many of its applications such as survey, mapping, agriculture, urban planning, telecommunications and package delivery.

One of the most popular UAVs used in an academic environment is the multirotor UAVs. This is due to its ability to take-off and land vertically and hover stationary during flight. However, one of the main problems for the quadcopter is the limited operating time, as most of the energy is consumed extensively in hovering. This problem also limits the flight range. Alternatively, traditional fixed-wing UAV, although are more energy-efficient and longer range, is lacking the advantage of multirotor UAVs (take-off and land vertically and hover stationary during flight).  The idea here is to model, simulate and control flapping wing UAV rather than typical fixed-wing or multirotor.

It is envisaged that this project will consist of the design and development of the mathematical model of a flapping wing UAV. This will allow some new control schemes to be evaluated in the simulation environment for the UAV.

Additional Project costs: N/A

Supervisors:   Dr Halim Alwi
Contact email:   h.alwi@exeter.ac.uk

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Project Title: Flight control system design using machine learning and artificial intelligence.
Project Description: Academic research in the area of small Unmanned Aerial Vehicles (UAVs) has received significant attention in the last few decades. This is driven by many of its applications such as survey, mapping, agriculture, urban planning, telecommunications and package delivery.

One of the typical UAVs used in an academic environment is the small fixed-wing UAV. There are many off-the-shelf components available that enable quick design, build and fly UAV. Off-the-shelf flight microprocessors provide a quick implementation for flight control typically using PID. The idea of this project is to use machine learning and artificial intelligence to identify the model and then help design and tune more advanced flight control systems. It is envisaged that this project will also consist of the design and development of the mathematical model of a UAV to allow new control schemes to be evaluated in the simulation environment for the UAV.

Additional Project costs: N/A

Supervisors:   Dr Halim Alwi
Contact email:   h.alwi@exeter.ac.uk

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Project Title: Smart Distribution System
Project Description: Smart Grids are at the centre of the future electricity network that utilises low carbon energy. Instead of traditional one-way energy transmission, Smart Grids utilise novel sensors and communication technologies to obtain a two-way communication channel between the utilities and customers to increase customer engagement in improving power quality and reliability.

In a traditional power network distribution network system has the least visibility even though it is the closest part to the customer. This is due various factors including the smaller number of customers being affected by each distribution substation, large number of substations compared to the transmission system and cost of monitoring/ communication is higher than component replacement.

This research will look into the implementation of Smart Distribution Substations overcoming the current challenges including the development of low-cost sensors, use of machine learning to combine multiple sensor data and implementation of communication protocols.

Additional Project costs: N/A

Supervisors:   Dr. Shanika Matharage and Prof. Zhongdong Wang
Contact email:   shanika.matharage@exeter.ac.uk

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Project Title: Chemical Ageing Indicators for Environmentally Friendly Power Transformers
Project Description: Mechanical strength of the winding insulation is the key component of a power transformer that decides the age-related failure of a transformer. However, due to difficulties with accessing the transformer to obtain insulation paper samples for any direct measurement of its strength it is common to use chemical indicators to predict the ageing state of power transformer insulation. 2-Furfural is one such ageing indicator commonly used in the industry for many decades. Traditional, power transformers used petroleum based mineral oil as the liquid insulation. However, with environmental and safety concerns ester based insulating liquids are gaining popularity in transformers used for both transmission and distribution voltage levels. Therefore, it is vital to study the ability to use these traditional ageing indicators for transformers with new alternative insulating liquids.

This project will study the ability of using 2-FAL for transformers built with alternative insulation materials through the studies of their generation from solid insulation, partitioning between liquid and solid insulation and the stability in the insulation system. Results from this research will develop new mathematical models to help transformer asset managers predict the ageing state of solid insulation for power transformers with alternative insulating liquids.

Additional Project costs: N/A

Supervisors:   Dr. Shanika Matharage and Prof. Zhongdong Wang
Contact email:   shanika.matharage@exeter.ac.uk

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 Project Title: Intelligent framework for impact based forecasting to strengthen societal resilience against hydrometeorological hazards

Project Description: Traditional flood risk management has been focusing on the prediction of flood disasters in order to develop measures to reduce the intensity and/or extent of hazards, which consequently may decrease the risk to a society. Nevertheless, hazards do not always pose risks to the locations where they are occurring. The cascading effects and the interconnectivity between different environmental and societal factors may turn a minor hazard into a catastrophe that affects a much wider area and population. The situation is more challenging when an extreme event hits and there are limited deployable resource for protecting vulnerable communities. Understanding of the scale, locations and timing of possible impact would be critical for decision makers to take adequate actions at right timing and places to maximise the effectiveness of hazard mitigations. The project will explore digital innovations to establish an intelligent framework, considering the complex interrelationships between various components or systems, to forecast the impacts of hydrometeorological hazards. Combing with vulnerability and probability, risk-based early warning can be issued to relevant groups such that related stakeholders can better plan for emergency response and allocate required resources to safeguard the regions at greater risks to avoid unnecessary casualties and losses.

Additional Project costs: N/A

Supervisors:   Albert Chen

Contact email:   a.s.chen@exeter.ac.uk

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The projects below are self-funded and therefore applicants will need to find external funding sources to cover tuition fees, living expenses’ and research costs (bench fees) associated with the project. 

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Project Title: Global consequences of climate changes in the polar regions
Project Overview: I am happy to hear from prospective students interested in pursuing a PhD on any aspect of polar climate variability and change, and its consequences for global weather and climate. Potential topics could include, but are not limited to: the causes of polar amplification; mechanisms of Arctic or Antarctic sea ice variability and change; the effects of Arctic warming on midlatitude climate and extreme weather; atmospheric teleconnections between the high and low latitudes; the role of sea ice in the global climate system.

Additional project costs:
N/A

Supervisors: Professor James Screen
Contact email: j.screen@exeter.ac.uk

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Project Title: Forecast performance analysis
Project Overview: A key stage in improving and applying environmental forecasting systems is analysing the performance of past forecasts. This can reveal the different ways and circumstances in which forecasts might be misleading, and how they might be improved. This project will extend existing statistical methodology to enable more detailed analyses of spatio-temporal environmental forecasts, such as those produced by weather and climate prediction systems. The project requires a student with a strong background in the mathematical theory of probability and statistics.

Additional project costs:
N/A

Supervisors: Dr Christopher Ferro
Contact email: c.a.t.ferro@exeter.ac.uk

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Project Title:  Dynamical Systems with Delay
Project Overview:  When a dynamical system is modelled by a differential equation with delayed arguments (look up the famous Mackey-Glass equation for an example) the dimension of the phase space (that is, the space of possible initial conditions) is infinite-dimensional. That is why even a single delay differential equation (DDE) can show chaos with many unstable Lyapunov exponents.
While the basic theory for systems with constant delay is well settled, systems in which the delay depends on the state still offer many challenging open problems. At the moment there is no rigorous theory extending the classical theory for ordinary differential equations to DDEs with state-dependent delay.
Depending on the inclination of the student the project can have theoretical, computational and modelling components. The primary supervisor currently maintains and develops the open-source software library DDE-Biftool, which is used by scientists and engineers to perform bifurcation analysis of problems with delays. The student can contribute to the further development of the numerical methods underlying DDE-Biftool, or they can exploit its newest developments to analyse problems arising in neuroscience (eg, reaction delays) and engineering (eg, control or machining problems)."

Additional project costs: N/A

Supervisors: Prof Jan Sieber
Contact email:  j.sieber@exeter.ac.uk

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Project Title:  Mathematical models of cell shape
Project Overview:  There are a wide range of cell shapes throughout nature, including capped-cylinders, spirals and branched structures. Further, these shapes often change when cells crawl, swim or engulf foreign particles. The underlying rules that control cell shape are not well understood, but include membrane tension, intracellular forces and the environment.

In this project, you will use a combination of mathematical modelling and computer simulation to study the factors that give rise to cell shape and its dynamics. A particular focus could be on investigating similarities and differences between different organisms, even between organisms from different kingdoms of life that are traditionally thought to behave in completely different ways.

This will be a multidisciplinary PhD and will involve using mathematics, biophysics and programming in combination with real biological data. You will have the opportunity to join an active, large group of researchers within the Living Systems Institute, who use a wide range of quantitative approaches to study numerous areas of biology and medicine.


Additional project costs: N/A

Supervisors: Dr David Richards, Prof Krasimira Tsaneva-Atanasova
Contact email:  David.Richards@exeter.ac.uk

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Project Title:  Modelling the Partially Ionised Solar Chromosphere, Mathematics
Project Overview:  The solar chromosphere is of great importance for understanding the energy flow and dissipation mechanisms in the solar atmosphere. We understand that magnetic forces are crucial in this layer, but the plasma is only partially ionised making the couple between the plasma and the magnetic field imperfect. In this project the student will explore and develop models of the coupling between the magnetic field and the fluid of the chromosphere to understand how observed dynamic phenomena are created and how the friction between charged species moving with the magnetic field plays a role in the heating of the chromosphere. The project will involve combining numerical modelling, theory, and observations to understand how fundamental magnetohydrodynamic (MHD) phenomena develop in a partially ionised system including regimes beyond those where a single fluid approximation holds.

Additional project costs: N/A

Supervisors: Prof. Andrew Hillier
Contact email:  a.s.hillier@exeter.ac.uk

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Project Title:  Impact of Climate Change on the Tropical Pacific and El Nino
Project Overview:  The Pacific Ocean is the largest ocean basin on Earth and is home to the biggest mode of interannual climate variability - the El Nino Southern Oscillation (ENSO). This project will examine aspects of how human-induced climate change will impact both the mean-state climate of the tropical Pacific, ENSO and its teleconnections to remote parts of the world. Specific questions could include (i) how do we reconcile recent observed La Nina-like trends with the tendency of models to produce El Nino-like patterns?, (ii) how do atmospheric processes involving surface fluxes and clouds change in the latest models?, and (iii) how do shifts in rainfall patterns lead to changes in tropical teleconnections?

Additional project costs: N/A

Supervisors: ProfMat Collins, Dr Rob Chadwick
Contact email:  M.Collins@exeter.ac.uk

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Project Title:  Fighting bacterial antibiotic resistance using mathematical modelling and analysis
Project Overview:  Increasingly quantitative descriptions of systems and processes in the life sciences require highly innovative mathematical tools and techniques in order to successfully address biological and biomedical challenges. The aim of this project is to develop and apply state-of-the-art mathematical tools and techniques to investigate antibiotics uptake in pathogenic bacteria and its implications for antimicrobial resistance.
Specifically, this project will build on our preliminary modelling work, recently published in https://doi.org/10.1039/D0LC00242A where we combine experiments and theory to describe drug accumulation in individual bacterium. Although the behaviour exhibited by the model agrees well with the experimental data, this is merely a starting point of being able to understand the mechanisms controlling antibiotic resistance quantitatively. In this project we will combine data science approaches and dynamical systems analysis to systematically investigate the processes governing antibiotics uptake and thus contributing to antimicrobial resistance.
 
Additional project costs: N/A

Supervisors:  Prof Krasimira Tsaneva-Atanasova, Dr Stefano Pagliara
Contact email: k.tsaneva-atanasova@exeter.ac.uk

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Project Title:  Predicting emotional states based on multimodal physiological signals
Project Overview:  In this project, we will use Network Physiology theory and Data Science approaches to analyse and model the response to audio, visual, and audiovisual emotional stimuli in healthy as well as participants with Post-traumatic stress disorder (PTSD) in order to identify biomarkers of PTSD. Post-traumatic stress disorder (PTSD) is a psychological response to the experience of stress resulting from traumatic events, especially life-threatening events. To this end, we will analyse and model data collected as part of an oddball task looking at the response to audio, visual and audiovisual emotional stimuli in healthy as well as participants with PTSD. In the oddball task the response to audio, visual and audiovisual emotional stimuli have been measured in the form of brain activity in the form of Electroencephalogram (EEG) as well as physiological responses such as skin conductance, heart rate or Electrocardiogram (ECG).

Additional project costs: N/A

Supervisors:  Prof Krasimira Tsaneva-Atanasova, Prof Anke Karl
Contact email:  k.tsaneva-atanasova@exeter.ac.uk

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Project Title: Modeling neuronal circuits in a ciliary micro-swimmer
Project Overview:  Studying flow responses in swimming organisms involves understanding of the neuronal and behavioural responses to environmental cues. A comprehensive, systems-level understanding of such responses is important to correctly interpret a wide range of phenomena in the life of aquatic organisms. In this project, we will use available data collected from the experimentally tractable micro-swimmer, larval Platynereis, to develop a network model of the whole-body circuit mechanisms controlling swimming. Specifically, based on Electron Microscopy (EM) reconstructions and swimming activity data we will derive a computational circuit model to further dissect how neuronal activity influences ciliary beating and other movements. We will analyse networks of excitable units to study the patterns of emerging activity given the network structures derived form EM reconstructions.

Additional project costs: N/A

Supervisors:  Prof Krasimira Tsaneva-Atanasova, Prof Gaspar Jekely
Contact email:  k.tsaneva-atanasova@exeter.ac.uk

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Project Title: A comparison of Bayesian neural networks and Gaussian processes for emulating complex numerical models
Project Overview:  In order to understand natural phenomena, for example in climate or epidemiology, we often turn to mathematical models. These typically are a set of partial differential equations derived from the laws of physics solved numerically. There are uncertainties in the model inputs and we would like to know how these propagate to the outputs. This involves running the model a large number of times. These models are computationally expensive so we use fast statistical approximations to the model, called emulators. Most emulators are based on Gaussian processes. This project will look at possible alternatives. In particular we will look into using Neural Networks. Recent developments in so-called Bayesian neural networks give a measure of uncertainty a vital component of an emulator. In this project you will develop emulators for complex numerical models using Neural Nets and compare them with emulators based on Gaussian processes.

Additional project costs: N/A

Supervisors:  Prof Peter Challenor, Dr James Salter
Contact email:  P.G.Challenor@exeter.ac.uk

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Project Title: Computational approaches to maximising lettuce yield in plant factories
Project Description: Plant factories, in which plants are cultivated in large, indoor structures under highly controlled conditions, are increasingly attracting attention as a new type of mass-cultivation method. This interest is primarily due to their significant potential in producing the extra food required to address global population growth, whilst also mitigating damage to the environment and promoting economic prosperity. However, plant factories are currently more costly to run, compared with conventional cultivation methods. A critical challenge is therefore developing techniques to efficiently and systematically determine the combinations of experimental factors that optimise plant growth.

This highly interdisciplinary PhD project will address this important challenge, with the aim of optimising the cultivation of an exemplar cyber-agriculture plant, Lactuca sativa (lettuce), within an established commercial large-scale plant factory. It will utilise expertise in the Akman group based at the Department of Mathematics (biological network modelling; optimisation; circadian systems biology) and the Keedwell group based at the Department of Computer Science (artificial intelligence; machine learning; optimisation). Furthermore, the proposed work will be carried out in partnership with the following collaborators of Akman’s: (i) Hirokazu Fukuda at Osaka Prefecture University – a world-leading plant factory researcher. Fukuda runs a facility that is currently producing 5000 plants per day, at which experiments will be conducted; (ii) Isao Tokuda at Ritsumeikan University, Kyoto, who has worked extensively with Fukuda on exploiting the synchronisation properties of hydroponic Lactuca growth to increase yield; and (iii) the Alan Turing Institute (ATI), the UK’s national centre for data science and artificial intelligence. Novel, domain-specific regression and optimisation methods will be developed during this project, based on combining machine learning models with evolutionary algorithms (EAs). In addition, the machine learning models developed to accelerate EA performance will be implemented using mogp_emulator, a package for Gaussian process emulation that is being developed by the ATI.

Additional Project costs: N/A

Supervisors:   Ozgur Akman, Ed Keedwell
Contact email:   O.E.Akman@exeter.ac.uk

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Project Title: Machine learning and optimisation for combined antibiotic treatments
Project Description: In biotechnology, a critical challenge is to efficiently and systematically determine the combinations of experimental factors that optimise target outputs. This highly interdisciplinary PhD project will address this important challenge, with the aim of demonstrating reproducible, closed-loop optimisation in an exemplar system with significant potential medical applications. It will utilise computational expertise in the Akman group based at the Department of Mathematics and biophysics expertise in the Pagliara laboratory at the Living Systems Institute, where experiments will be conducted.

The proposed work will be carried out in partnership with two collaborators of Akman’s: the London-based biotechnology company Synthace Ltd, who are world-leaders in laboratory automation and the Alan Turing Institute (ATI), the UK’s national institute for data science and artificial intelligence. Synthace are developing Antha, a programming language and software platform designed to make reproducible, scalable workflows that can be edited and shared. Novel, domain-specific optimisation methods will be developed for Antha implementation, based on combining machine learning models with evolutionary algorithms (EAs). In addition, the machine learning models developed to accelerate EA performance will be implemented using mogp_emulator, a package for Gaussian process emulation developed by the ATI.

 Additional Project costs: N/A

Supervisors:   Ozgur Akman, Stefano Pagliara
Contact email:   O.E.Akman@exeter.ac.uk

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Project Title: Statistical post-processing of ensemble forecasts of compound weather risk

Project Description: Probabilistic weather forecasts are typically derived from ensemble forecasts generated by numerical weather prediction models. An ensemble is a collection of deterministic forecasts, where the forecasts differ in the initial conditions supplied to the model and/or the numerical weather prediction model used. Demand for such forecasts is increasing as they provide users with a basis for risk-based decisions. It is crucial that probabilistic forecasts are well calibrated. Decisions based on poorly calibrated forecasts could lead to inappropriate actions and significant losses. However, forecast ensembles are still biased both in location and dispersion. They tend to be underdispersive, leading to overconfident uncertainty estimates and an underestimation of extreme weather events.

The project will develop novel multivariate statistical techniques for recalibrating forecast ensembles that capture spatial, temporal and cross-variable dependence. These will improve probabilistic prediction of compound weather risk. A particular emphasis will lie on high-impact extreme weather events.

The research will be conducted in close collaboration with the Met Office as project partner. We will use historical data from the Met Office's ensemble prediction system MOGREPS together with the corresponding verifications. Meteorological variables of interest are UK temperature, surface pressure, wind speed and precipitation.

Additional Project costs: N/A

Supervisors:   Dr Frank Kwasniok (Department of Mathematics, University of Exeter), Dr Chris Ferro (Department of Mathematics, University of Exeter), Dr Gavin Evans (Met Office), Dr Piers Buchanan (Met Office)

Contact email:   F.Kwasniok@exeter.ac.uk

 

The projects below are self-funded and therefore applicants will need to find external funding sources to cover tuition fees, living expenses’ and research costs (bench fees) associated with the project.

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Project Title:   Statistical Design of Experiments for accelerated component testing in offshore renewable applications
Project Overview:  The offshore wind industry has resorted to very specific performance and durability testing of the individual wind turbine components (rotor blades, drivetrain, nacelle and foundation) that aim to replicate and accelerate the in-situ load conditions.

This PhD project aims to utilise the statistical Design of Experiments approach to develop new methods that are capable to devise the most efficient test regimes for offshore energy applications. Aspects to consider include the stochastic behaviour of the load environment as well as the possibility to reveal new and largely different failure behaviours for these new, often unproven applications.

The Design of experiments approach aims to identify, select and schedule the combinations of governing factors (e.g. frequency, load range, sample properties) for the test regime to achieve the test objective with a minimal use of resource (i.e. cost, test time, sample number), whilst maintaining the statistical significance of the results.

This involves building a statistical model that approximates the relationship between the governing factors on the desired component response (e.g. lifetime). This in turn allows to quantify the uncertainty of the experiments themselves as well as to make a prediction on the component response.

Additional project costs:  TBC

Supervisors:
Prof Philipp Thies, Prof Peter Challenor
Contact email: 
P.R.Thies@exeter.ac.uk

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Project Title: Highly energy efficient building envelop for low/zero energy building
Project Overview:  Energy consumption by building sector is one of the utmost concern, recently. According to IEA, in 2019, building sector consumed around 128 EJ of energy, primarily from the burning of fossil fuel. Since 2010, this energy consumption increased at an average growth rate of 0.7%, thereby, increasing the CO2 emission from building by ~5%. Energy consumption from building sector is considered even higher than the transport sector. Building consumes energy due to heating, cooling and artificial lighting load. Among the different building envelopes, windows are the weakest components, which must be replaced by highly efficient technology. Inside a building, we spend almost 80-90% of our lives, hence the provision of interior comfort is an essential criteria for different types of building including commercial, residential, or hospital. Building window has an influential impact on health and well-being of the occupant.
Presently available advanced windows include highly efficient constant and switchable transparent windows. In this work, thermal, optical, daylight, electrical, thermal and visual comfort of a suitable window for different climatic conditions will be investigated. Small prototype will be developed and will be characterised at the university rooftop.

Additional project costs:
£2000

Supervisors: 
Dr Aritra Ghosh, Prof Tapas Mallick
Contact email: a.ghosh@exeter.ac.uk

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Project Title:  Building integrated photovoltaic for adaptive building application
Project Overview:  Energy consumption has increased extensively due to the recent development of industry and agriculture. The majority of this energy is generated from fossil fuel, which causes adverse environmental hazards. To address this detrimental issue, renewable energy generation by using onsite benign power generation from photovoltaic (PV), installed in a building, is one of the potential approaches, which reduces the necessity of large land requirement and the transmission power losses. Thus for urban buildings, building-integrated PV (BIPV) is one of the appropriate solution because of its aesthetic appearance and ability to offset the initial cost.
BIPV in a building replaces traditional wall, roof, and window by semi-transparent glazed window or can be installed as large glazed façade for commercial buildings. Semi-transparent BIPV glazing limits entering solar heat gain, daylight and generates benign electricity where, PV can be semi-transparent or spaced type opaque materials, sandwiched between two glasses. In this work, novel switchable BIPV will be explored using thermal, electrical and daylighting characteristic along with overall building energy, levelized cost of energy (LCOE), and life cycle analysis (LCA) will also be explored.

Additional project costs:  £2000

Supervisors:
Dr Aritra Ghosh, Prof Tapas Mallick
Contact email: 
a.ghosh@exeter.ac.uk

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Project Title: Environmental impacts of critical raw materials needed for carbon neutrality
Project Overview: To achieve carbon neutrality, we need to deploy low carbon technologies such as renewable energy and electric vehicles on a large scale globally. These technologies will in turn need vast amounts of critical raw materials such as lithium, cobalt and rare earth metals. However, the environmental impacts of producing these materials at the scale required for carbon neutrality are poorly understood currently. This could lead to an underestimation of the embedded carbon in the low carbon technologies, jeopardising climate goals. Moreover, it could potentially lead to problem shifting from carbon to other environmental impacts. This project will use life cycle assessment (LCA) to evaluate environmental impacts of critical raw materials under different global carbon emission pathways.

Additional project costs: N/A

Supervisors: 
Dr Xiaoyu Yan, Prof Frances Wall
Contact email: 
Xiaoyu.Yan@exeter.ac.uk

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Project Title: Predicting and analysing soiling losses for Photovoltaic system
Project Overview:  Historically, global energy security of different countries came from coal and crude oil production and availability. However, these energy resources produce energy by directly polluting the environment. Contrariwise, global electricity demand is expected to be twice as high in 2050 as it is at present. Thus, dependency on renewable energy resources is growing and particularly photovoltaic is gaining prime importance. It was found that, at the end of 2018, global installed solar photovoltaic (PV) capacity exceeded 500 GW, and an additional 500 GW of PV capacity is to be installed by 2022–2023, bringing us into the era of TW-scale PV. Notably, photovoltaic power output largely depends on local climatic conditions and the orientation of PV devices.
However, non-ignorable dust (soiling) deposition factors limit PV power generation by creating a shielding effect on PVs, which decreases solar transmission through the glass of the PV surface. Based on the particle diameter and rate of deposition, the annual PV power production is affected significantly. In this work, soiling impact on global PV power generation will be investigated employing outdoor real environment and optoelectrical indoor characterization. The soiling impact on all three generation PVs will be explored.

Additional project costs: 
£2000

Supervisors:
Dr Aritra Ghosh, Prof Tapas Mallick
Contact email: 
a.ghosh@exeter.ac.uk

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Project Title:  Techno economic analysis of Bifacial PV systems
Project Overview:  Solar photovoltaic (PV) systems have become a major contributor to global electricity generation with more than 600 GWp of accumulated installed capacity as of 2019. The majority of current PV installations employ monofacial crystalline silicon PV modules with a fixed-tilt system setup. Bifacial modules have ability to collect light not only from the front, but also from the rear side, which makes them advantageous for power generation. Recent research indicates that bifacial modules can potentially increase the system yield by 20–30% over monofacial modules. The International Technology Roadmap for Photovoltaic notes that, as of 2020, bifacial PV cells accounted for about 20% of the total world PV cell market and that, by 2030, is expected to increase to 70%.
Though it has enormous possibility, real experiment employing bifacial PV system for grid connected and building integrated application is still limited. In this work, thermo-opto-electrical behaviour of bifacial PV system will be evaluated using simulation techniques. Real time experiments to understand the possibilities and challenges associated with bifacial PV system will also be explored.

Additional project costs:  £2000

Supervisors: 
Dr Aritra Ghosh, Prof Tapas Mallick
Contact email:
a.ghosh@exeter.ac.uk

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Project Title: Smart Composite Material for Building Energy Efficiency

Project Description: The mounting demand for better energy efficiency and visual comfort of buildings has led to the development of innovative, high performance smart glazing systems using smart composite material.  Our vision is to undertake an ambitious innovative research program developing new technology to significantly reduce energy demand in the built environment at an acceptable cost. The goal will be achieved by reducing heat loss, controlling incoming solar radiation to maximise solar gain, minimise heat loss in winter and reverse it by flipping windows in summer while ensuring the best natural lighting conditions with no glare. This research program will develop advanced glazing technology with the aim to have U-values down to 0.4 W/m2K1 while maintaining comfortable daylight environments and to reduce annual net energy consumption by 30-40% for buildings. This will be achieved by developing a multi-fold smart composite based on optimised matrix of phase change materials (PCM) to enhance thermal capacitance, transparent insulating materials (TIM) to increase thermal resistance, transparent infrared absorber (TIA) to absorb IR radiation and  thermochromic materials (TCM) to control light transmission and along with infrared reflective coating to reduce heat loss and gain through transparent envelope of built environment. The outcome of this research will enable us to create technological pathways towards achieving energy positive buildings in the UK.

Additional Project costs: N/A

Supervisors:   Dr Asif Tahir
Contact email:   a.tahir@exeter.ac.uk

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Project Title: Emerging 2D Transition Metal Chalcogenide Nanomaterials for Solar Energy Conversion

Project Description: The research programme aims to investigate two-dimensional (2D) chalcogenides MX2 nanomaterials for sustainable Artificial Photosynthetic (AP) water splitting device to respond to the current energy and environment crises. This innovative and timely project aims to deliver breakthrough design and development of 2D transition metal chalcogenides MX2 nanomaterials based photoelectrodes for spontaneous water splitting by engineering suitable aligned band structures. The rationale behind this challenging approach is to envisage band structure of photoelectrodes theoretically through DFT simulations and benchmarking experimental validation with controlled nanoarchitecture fabrication using state of the art techniques.  The adventurous project intends to achieve over 10% solar to hydrogen (STH) efficiency by precisely aligning bandedge positions of photoelectrode, nanoarchitecture tuning and surface modification. The theoretical simulation, fabrication, material characterisation, study of energy conversion mechanisms, electrode/electrolyte interface, charge carrier dynamics and catalytic reaction carried out in this transformative project will provide a profound understanding and firm basis to construct a commercially feasible AP device. The ground breaking multidisciplinary nature of the proposed project is not limited to AP water splitting but the material design, fabrication and material characterisation strategies used in this project will feed into other frontiers of advanced materials research such as CO2 photoreduction, sensors and photocatalysis.

Additional Project costs: N/A

Supervisors:   Dr ASIF TAHIR, Prof. Tapas Mallick
Contact email:   a.tahir@exeter.ac.uk

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Project Title: Design and development of Hydrogen and Oxygen Evolution Reaction Catalysts for Sustainable Fuel (H2) Production

Project Description: Hydrogen is a promising alternative to unsustainable fossil fuels due to its vital role in ammonia and clean-burning fuel production. About 96% of the world’s hydrogen comes from the reformation of fossil fuels, which utilize high energy, followed by serious CO2 emissions. Efficient and sustainable H2 can be produced with the help of state-of-the-art electrocatalysis from water splitting; a combination of two half-reactions, the oxygen evolution reaction (OER) which occurs at the anode, and hydrogen evolution reaction (HER) at the cathode. Currently, platinum-based materials (PGM) are efficient electrocatalyst for water electrolysis, however, scarcity and high cost limits their large-scale hydrogen production.

We will investigate non-PGM-based catalysts for the development of high-performing, stable, and yet low-cost. The key parameter for designing an efficient electrocatalyst is the determination of overpotential (η), the lower the values of η of a catalyst the higher will be the oxygen/hydrogen evolution and vice versa.

In this project, first, we will understand the catalyst properties that control activity, selectivity, and stability by combining catalyst synthesis and electrochemical performance testing with physical and chemical characterization as well as computational and theoretical modeling (DFT). These combining insights will help us to design new electrocatalyst materials with improved performance.

 Additional Project costs: N/A

Supervisors:   Dr ASIF TAHIR, Prof. Xiaohong Li
Contact email:   a.tahir@exeter.ac.uk

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Project Title: Nanoscale Engineering of Semiconductor Heterostructures for Solar Fuel Device

Project Description: Clean energy and sustainable environment are grand challenges that the world is facing, and transportable and storable fuels (chemical fuel) from renewable resources can make a vital contribution to address these challenge. Chemical fuels (solar Fuel) such as hydrogen produced from renewable resources (water and sunlight) and chemicals such as methanol, ethanol, methane and syngas by photoreduction of CO2 back to fuel can make solar energy highly distributable, from small to large scale applications. An ideal technology for solar-to-chemical energy conversion process is artificial photosynthesis (AP), which aims to emulate natural photosynthesis using man made materials. However, it remains a significant challenge to construct an efficient AP device due to the lack of suitable materials which fulfil AP requirement. Overcoming the limitations of currently-available materials is a major motivation for the proposed project. The proposed project is focused on the development of AP photocatalysts based on heterostructure nano-architectures where a single particle will be able to carry out both oxidation and reduction reactions required to split water for solar fuel (hydrogen) generation.

Additional Project costs: N/A

Supervisors:   Dr Asif Tahir, Prof. Tapas Mallick
Contact email:   a.tahir@exeter.ac.uk

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The projects below are self-funded and therefore applicants will need to find external funding sources to cover tuition fees, living expenses’ and research costs (bench fees) associated with the project.

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Project Title:  Nonreciprocal devices: optical isolators and circulators from theory to applications
Project Overview:  Reciprocity in the animal kingdom gave rise to the evolution of reciprocal altruism: “you scratch my back, and I will scratch yours”. Introducing the concept of nonreciprocity into metamaterials research also allows one to profit from nonreciprocal interactions, with immediate technological applications. Non reciprocal devices, such as optical circulators and isolators,rely on the directional transfer of energy and information at the nanoscale. Furthermore, the realization of nonreciprocal waveguides will lead to extraordinary propagation lengths, being immune to backscattering. In this project, we will construct theoretical models inducing nonreciprocity in metamaterials, for example those built from nanoscopic lattices of meta-atoms. We will consider how topology, dissipation and various symmetries can be employed to create a new class of nonreciprocal metamaterials with extraordinary transport and directional properties. Our work will be done in close collaboration with the leading experimentalists, where the novel phenomena that we discover can be simulated by, for example, acoustic waves or microwaves. The results of this project should guarantee future applications in wave physics, metamaterials and nanotechnology, particularly via the exploitation of the unidirectional flow of excitations.

Additional project costs:  N/A

Supervisors:
Dr Charles Downing
Contact email: 
C.A.Downing@exeter.ac.uk

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Project Title:  Metamaterials for enhanced radar detection
Project Overview: 
Over the last 10 years the world around us has become ever more densely populated by a host of autonomous machines. Although these technologies open up a vast array of opportunities, they also create significant problems around the area of detectability: machines are getting smaller, while the electromagnetic environment is becoming increasingly congested. Detecting and identifying small objects such as remote drones and small ‘picosat’ satellites via conventional radar is difficult due to their small radar cross section (RCS).   This project will address this challenge by designing 2D and 3D metamaterial structures to improve or otherwise dictate the RCS of small objects. The project will start at a quite fundamental level, examining novel highly scattering structures through simulation and experiment, and will later have the potential for collaboration with industrial partners to integrate these materials into an low cross section technology such as drones or picosats. This work will be closely tied to a project sponsored by the Royal Academy of Engineering, and the successful applicant will enjoy a close working relationship with the academics on that project.

Additional project costs:  £20000

Supervisors: Dr Alexander Powell, Prof. Alastair Hibbins
Contact email:  a.w.powell@exeter.ac.uk

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Project Title:  Anisotropic 3D Metamaterials inspired by Shrimp-Eye Reflectors
Project Overview:  Nature is a constant source of inspiration for science, and this project will develop 3D metamaterials inspired by curious structures found in the retina of certain shrimp species. These take the form of hollow spheres made of high refractive index plates, structured in a way that produces a much greater refractive index in the radial direction than the tangential (radial anisotropy). This leads to manipulation of the natural resonances of these spheres, which increases their backscatter significantly. 

In the course of this project the student will study such anisotropic systems though simulation and theory, and will design demonstrators operating at microwave frequencies to show both maximised scattering and the potential for zero scattering (cloaking) conditions. They will 3D print samples and test them in our specially developed anechoic chamber.

There is also great potential for this technology to be applied to the development of novel dielectric antennas, as well as ample opportunities for engagement and collaboration with industrial partners.

This work will be closely tied to an existing project sponsored by the Royal Academy of Engineering, and the successful applicant will enjoy a close working relationship with the academics on that project.

Additional project costs:  £20000

Supervisors: Dr Alexander Powell, Prof. Alastair Hibbins
Contact email:  a.w.powell@exeter.ac.uk

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Project Title:  Quantum optimal control to decipher magnetoreception
Project Overview:   The navigational skills of migratory songbirds, travelling thousands of kilometres each year, are astounding. The successful completion of these magnificent voyages depends crucially on the birds’ ability to sense the Earth’s magnetic field. Exactly how this magnetic sense works remains a mystery. In any case, the accumulated experimental evidence suggests something extraordinary: the birds’ compass sense appears to rely on quantum coherent dynamics in a pair of radicals formed in receptor proteins in their eyes. There, in the birds’ retinae, coherent spin dynamics are believed to be driven by magnetic interactions, which imparts a directional magnetic sensitivity on a chemical reaction to give the birds magnetic vision.

Project aims: The identity of the active radical pair is still fiercely debated. The idea of this project is to probe into the possibility of quantum optimal control approaches to distinguish competing hypothesis. In particular, oscillating magnetic fields can be applied to govern the radical spin dynamics externally, and thus control the reaction outcomes. Your task will be to develop novel tests to distinguish competing hypothetical mechanisms and radical identities based on purpose-shaped radiofrequency pulses using computer simulations.

Additional project costs: N/A

Supervisors:  Dr Daniel Kattnig
Contact email:  d.r.kattnig@exeter.ac.uk

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Project Title:  Finite element modelling of the endplate in the human spine
Project Overview:   This project will further our understanding of painful spinal disorders by modelling the endplate junction between the bones and discs of the spine to determine, for the first time, the role of this junction on the stresses and strains in the surrounding tissues.

Nearly one in ten people develop a painful disorder with their spine. In many cases, the disorder involves changes in the geometry and properties of the spinal tissues. These changes are associated with altered stresses and strains. A key question is whether the changes are a cause, or an effect, of the disorder.

In this project, we will investigate the role of a specific tissue, the endplate. The endplate is a structure located at the junction between the discs and bones. It is important for transferring stress between these two components.

The project's first part will be to create a finite element model to represent the endplate and its adjacent disc and bone. The model will be used to determine how endplate shape and structure relate to stress and strain in the endplate, disc and bone. An adaptive process will be implemented to understand the association between tissue changes and altered spinal stress and strain.

Additional project costs: £5000

Supervisors:  Dr Judith Meakin, Dr Junning Chen
Contact email:  j.r.meakin@exeter.ac.uk

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Project Title:   Quantum Sensing with Spins in 2D Semiconductors
Project Overview:  Precision measurement underpins science and technology, and novel sensors that push the fundamental limits of accuracy and precision are required for applications ranging from nano-electronics to medical imaging. Colour centres have atom-like electronic transitions that can be probed with optical and microwave techniques, and thanks to a spatial extension on the scale of the atomic lattice, they can provide an exquisite probe of their local environment. In this project, you will develop an integrated microwave and photonic platform to control and investigate spins in 2D materials, with the ultimate aim of building a new generation of sensors with the highest possible sensitivity and spatial resolution

Additional project costs: £4000

Supervisors:  Dr Isaac Luxmoore
Contact email:  i.j.luxmoore@exeter.ac.uk

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Project Title: The formation and evolution of stellar clusters

Project Description: Stellar clusters are the main building blocks of galaxies. Advances in numerical calculations of galaxies and cluster formation, and new instruments are now allowing us to study how young clusters evolve, and in particular how stellar feedback (e.g. ionisation, winds, supernovae) expels gas from clusters. Our group works on numerical simulations of cluster formation and evolution in spiral arms, and we also have one member who is an observer. We would be keen to hire a PhD student who is interested in working at the interface of observations and simulations. We are involved in international observing collaborations to study clusters and the surrounding gas, including a recent successful JWST proposal to study ionisation. This project would involve converting simulations into HI, CO and Halpha emission maps (e.g. using the Exeter based radiative transfer code TORUS) through which we can compare for example ionisation regions in simulations with those observed. The project would also involve trying to reproduce particular star forming regions through simulations. The main requirements are a first degree (2:1 or equivalent) in a related subject (Physics, Astronomy, or Maths) and some experience in programming (ideally Python, C, or Fortran).

Additional Project costs: N/A

Supervisors:   Clare Dobbs

Contact email:   C.L.Dobbs@exeter.ac.uk

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