MSc Neuroscience (Data Science)
Please note: This page is for 2027 entry. Click here for 2026 entry.
| UCAS code | 1234 |
|---|---|
| Duration | 1 year blended full time |
| Entry year | 2026 |
| Campus | St Luke's Campus |
| Typical offer | 2:2 honours or equivalent in a relevant science subject. |
|---|---|
Why study MSc Neuroscience (Data Science) at Exeter?
- Gain cutting-edge expertise in neuroscience with the option to specialise in advanced data science methods.
- Learn from leading researchers exploring brain function, behaviour, and neurological disease.
- Develop practical skills in laboratory techniques, statistics, programming, and machine learning.
- Conduct your own research project, applying theory to real-world scientific questions.
- Graduate prepared for PhDs, research careers, or roles in healthcare, biotech and data-driven industries.
Fast Track (current Exeter students)
Contact
Programme Directors: Dr Emma Dempster and Dr Talitha Kerrigan
Web: Enquire online
Phone: +44 (0)1392 72 72 72
Small group learning, independent learning, teamwork, collaboration and communication
Major capital investment in new buildings and state-of-the-art facilities
Research-inspired teaching
Vibrant and active research student community supported by excellent pastoral and academic staff
Entry requirements
Minimum 2:2 honours or equivalent in a relevant science subject. Relevant subjects include biological sciences, medical sciences, cell biology, anatomy, microbiology, neuroscience, pharmacology, physiology or molecular biology.
Please also see our guidance on essential documentation required for an initial decision on taught programme applications.
Entry requirements for international students
English language requirements
International students need to show they have the required level of English language to study this course.
The required IELTS test scores for this course fall under Profile B2.
Please visit our English language requirements page to view the required test scores and equivalencies from your country.
Course content
This MSc provides a comprehensive foundation in translational neuroscience while equipping students with essential data science skills for modern research. You will develop the ability to critically evaluate and analyse complex biological datasets using tools such as statistical modelling, machine learning and scientific programming. These skills are applied in an extended data-driven research project, undertaken with one of our world-leading neuroscience teams, giving you the chance to work with real data and contribute to cutting-edge discoveries.
Core subject areas include molecular and cellular neuroscience, neurodegenerative disease, and behavioural and systems neuroscience. Teaching is delivered through a blended approach, combining online lectures, bespoke tutorials, laboratory visits and practical exercises, all supported by the University of Exeter’s electronic learning environment (ELE). The programme consists of six core modules, one optional module, and a 60-credit dissertation, and can be studied full time over one year.
For those interested in exploring neuroscience from a broader perspective, we also offer the MSc Neuroscience, which provides a comprehensive understanding of the field without the dedicated data science element. Together, these programmes offer flexible routes into neuroscience research and careers, allowing you to tailor your studies to your specific interests and aspirations.
Please note that the module information displayed here is subject to change.
165 credits of compulsory modules, 15 credits of optional modules.
You must select either HPDM171 or HPDM172.
Compulsory modules
| Code | Module | Credits |
|---|---|---|
| Compulsory 1 | ||
| Statistics for Health and Life Sciences | 15 | |
| Molecular and Cellular Neuroscience | 30 | |
| Seminars in Neuroscience | 15 | |
| Behavioural and Systems Neuroscience | 15 | |
| Neurodegenerative Disease - Bench to Bedside | 15 | |
| Compulsory Choice 2 | ||
| Coding in Python for Health and Life Sciences | 15 | |
| Computational Skills for Health and Life Sciences | 15 | |
| Compulsory 2 | ||
| Research Project - Data | 60 | |
HPDM182: Statistics for Health and Life Sciences
This module provides a broad introduction to statistical analysis for health and life science applications. The module starts by considering the different stages of a statistical investigation and emphasising the importance of problem formulation. The module highlights the benefits of exploratory data analysis based on descriptive statistics and graphs. Key concepts in probability theory and the role of statistical distributions in modelling health data will be covered. The core part of the module provides a foundation in regression modelling to include simple linear regression, logistic regression, survival analysis and models that account for complex temporal and hierarchical data structures. Embedded through the module is a strong emphasis on the critical evaluation of statistical methodology and interpretation of analysis results in the context of the specific health application. Throughout this module, you will gain practical experience of statistical computing using the R software environment and exposure to case studies based on real-world health data.
NEUM001: Molecular and Cellular Neuroscience
Our brains control our physiology, cognition, and behavior through a vast array of signaling pathways within and between cells, the coordinated activity of which form the basis of neural networks. In this module you will be introduced to the primary cell types in the central nervous system and the electrical and biochemical signaling pathways that enable communication between them. With focus on the primary research literature, these concepts will be explored in the context of experimental tools used in the laboratory and beyond. Taught by a combination of online lectures and interactive small group seminars, the neuropharmacological and neurophysiological concepts learned in this module provide a fundamental grounding in molecular and cellular neuroscience.
This module aims to acquaint you with several of the core principles and cutting-edge research in neuroscience. The core content will include neuroanatomy, intercellular communication, neuropharmacology, the molecular and cellular biology of synaptic plasticity, development and regeneration of the nervous system, integrative mechanisms, perception and cognition, sensation and molecular mechanisms and consequences of nervous system injury. You will also learn about how advances in basic research are driving the development of novel therapeutics for CNS disorders.
NEUM002: Seminars in Neuroscience
This module will introduce students to essential methods and skills utilised in research, which are important to understand for your development as a neuroscientist. You will learn about the scientific method and contemporary research methods, as well as computational modelling in neuroscience. You will receive teaching in different key areas and current neuroscience techniques, and presentation skills. These skills will be taught through a series of lectures and workshops from expert researchers.
This module aims to provide you with the essential knowledge and skills needed to perform cutting-edge neuroscience research with 'real-world' applications and to support you with your individual research project. These skills will be assessed at the end of the module with a presentation focusing on one of the neuroscience techniques covered in the module.
NEUM003: Behavioural and Systems Neuroscience
Physiology, cognition, and behaviour are complex processes orchestrated by the brain. This research-led module focuses on understanding how neural circuits initiate and/or regulate these processes including via interactions with the rest of the body and the broader environment. Through a combination of lectures, workshops, and seminars you will be introduced to our latest understanding of cognitive processes, the neural regulation of physiology, and resultant behavioural responses, and explore how these processes go awry in disease.
This module aims to bridge the gap between synaptic physiology and cognitive neuroscience to explain how the activity of groups of neurons can directly impact the behaviour of an organism. It will focus on understanding the neural basis of several inherent systems that are common across different organisms. Along with lectures and journal club sessions the module will embed the knowledge for understanding and evaluating experimental studies that involve behavioural neuroscience.
NEUM004: Neurodegenerative Disease - Bench to Bedside
This module focuses on the neurobiology of neurodegenerative disorders. Specifically, the module explores the ways in which recent research has answered questions about the mechanisms of neurodegeneration and more generally how ageing affects the nervous system, yet also poses new questions. In particular, the module highlights the potential for further progress in deciphering and repairing neural circuitry by considering some of the reasons effective treatments for many neural disorders remain elusive.
Whilst the module's precise content may vary from year to year, an example of an overall structure is as follows. The module focuses on important neurodegenerative disorders, utilising these to understand both pathology and normal physiology. The course is delivered by leading experts working in each of these disorders and will allow you to work with these researchers to identify key outstanding questions in the area of neurodegeneration and formulate a literature review to investigate your chosen disease area. This module will equip you with the theoretical, analytical, and methodological skills necessary for further postgraduate work or study in industrial or academic environments.
HPDM171: Coding in Python for Health and Life Sciences
Modern health research is becoming increasingly focused on the analysis of large, complex datasets. To extract meaningful information from such datasets, health data scientists often use computer programming languages to create bespoke analysis pipelines. Python is the most popular programming language for this task, making it a widely transferrable and employable skill.
This module assumes no prior knowledge of Python or any other computer coding language. We will be teaching Python from the ground up, starting with basic structures and objects available within Python, then developing more complex routines. When the fundamentals are established, you will learn how to manage and visualise data in Python. At the end of the course, you will learn how to perform machine learning tasks in Python, and come out of the module with general transferable computing and code-writing skills that will help you learn new languages quicker.
The overall aim of this module is to introduce students from a non-computing background to computer programming in Python, a common language for health data science. You will learn practical coding skills focused on developing the necessary skills to analyse data.
HPDM172: Computational Skills for Health and Life Sciences
Health data science is a complex field requiring a wide range of computing skills. For example, increasingly, many health datasets are hosted on cloud computing resources and requiring specialist software and multidisciplinary teams to access them. This module complements the Introduction to Python for Health Data Scientists module, with the aim of broadening the scope of the tools available to you as a data scientist. By the end of the module, you will have learned the following skills:
- Cloud computing using the Openstack system
- Computational thinking, including how to design an algorithm and planning programming using pseudocode
- Navigating the Linux command line
- Querying relational databases using SQL
- Ethical and effective use of generative AI
- The benefits of and how to use Git and GitHub for collaborative coding and version control
This module requires no previous knowledge of any of the required skills, although general computer skills will be beneficial.
The aim of this module is to provide a solid foundation in basic computational thinking and provide essential skills in widely used operating systems and computer software.
HPDM042: Research Project - Data
In this module you will apply and extend your existing knowledge and skills by undertaking an independent research project aligned with your degree programme (MSc Neuroscience, Health Data Science or Genomic Medicine). Projects are selected from a diverse portfolio designed to reflect a wide range of scientific interests and programme specialities. Depending on your programme, projects may involve laboratory-based research, a systematic review, or in silico approaches such as data analysis, computer modelling or bioinformatics. Projects are undertaken within Exeter’s leading research groups and may include collaboration with partners including the National Health Service, pharmaceutical companies and health data organisations.
Optional modules
| Code | Module | Credits |
|---|---|---|
| Optional 1 | ||
| Genomics of Common and Rare Inherited Diseases | 15 | |
| Bioinformatics, Interpretation and Data Quality Assurance in Genome Analysis | 15 | |
| Epigenetics | 15 | |
| Clinical Trials | 15 | |
| Child and Adolescent Mental Health | 15 | |
| Advanced Immunopathology | 15 | |
| Social Psychology | 15 | |
| Clinical Psychology | 15 | |
| Advances in Clinical Psychology and Neuroscience | 15 | |
HPDM037: Genomics of Common and Rare Inherited Diseases
This module is available either via blended learning with contact days on-campus supported by online learning, or as fully distance learning via our online platform.
This module explores the genetic basis of common and rare inherited disorders. The principles and practice of medical genetics and genomics, and the management and treatment of patients and their families will be discussed. Utilizing exemplars, the module demonstrates the clinical utility of genomic data in healthcare settings. You will learn about contemporary approaches used to identify genetic causes of disease, with a focus on rare inherited diseases.
The module will also address the integration of genomic data into clinical pathways, emphasizing the impact of advances in genomic technologies on patient care. The role of genomics in care pathways will be explored from both patient and family perspectives, as well as the diagnostic and therapeutic implications of genomic data. Additionally, you will learn to identify patients with unmet diagnostic needs who may benefit from exome or genome sequencing and will be introduced to the complexities of interpreting genomic data in clinical contexts. The module will also cover key initiatives such as the development of genomic medicine services, and the infrastructure supporting incorporation of genomic testing into the NHS.
HPDM041: Bioinformatics, Interpretation and Data Quality Assurance in Genome Analysis
One of the key challenges in genomic medicine is to interpret large-scale sequencing data effectively in order to arrive at an accurate genetic diagnosis. The aim of this module is to provide you with an in-depth understanding of how this process is conducted. You will learn how large-scale genomic data is analysed and interpreted, as well as develop a practical understanding of how bioinformatic and statistical tools are used.
The module will cover the fundamental principles of bioinformatics and data quality assessment as applied to clinical genomics. You will use a range of software packages and in silico prediction tools, alongside genomic and clinical databases. You will learn how to apply these tools to evaluate the quality of a sequencing data set, align sequencing reads to a reference genome, identify genetic variants, and filter variants with evidence of pathogenicity. Theoretical sessions will be coupled with practical workshops and self-paced assignments, where you will get to perform a range of data bioinformatic analyses on real-world data.
By the end of the module, you will be able to use bioinformatic tools to critically interpret real-world data and to accurately report your findings in a diagnostic context.
HPDM049: Epigenetics
This module is delivered through a blended learning format with scheduled on-campus contact days, supported by online learning resources available through the University’s virtual learning platform. The module introduces the structure and function of the human epigenome, including key regulatory mechanisms such as DNA methylation, histone modification and chromatin remodelling, and their role in controlling gene expression. You will examine how the epigenome interacts with the genome and how epigenetic regulation contributes to normal cellular function. Building on these core principles, the module explores the role of epigenetic variation in human health and disease. You will investigate how the epigenome changes with ageing and in response to environmental and psychosocial exposures, and how these changes may influence disease risk and progression. The application of epigenetics in diagnosis, treatment and monitoring of disease, particularly in areas such as cancer, will also be examined. The module will also introduce the genomic technologies and bioinformatics approaches used to study the epigenome, highlighting how epigenomic data can contribute to understanding disease mechanisms. Throughout the module, current challenges and limitations in epigenetic research will be critically discussed, alongside emerging developments in the field.
HPDM056Z: Clinical Trials
This is an online module.
This module will focus on clinical trials in an applied health research setting, with a focus on current trends in clinical trial design. You will learn how to evaluate health care technologies, including complex interventions, using a range of observational and experimental trial methods, from standard randomised clinical trials to pilot/feasibility studies, cluster trials, stepped wedge, observational and non-randomised designs. On top of covering different trial designs, through structured practical sessions, you will learn how to navigate the intricate connections between research ethics, sponsor and governance; to design a case report form; to plan and achieve successful recruitment; to implement good project management skills. You will develop competencies in the design, conduct, analysis and interpretation of interventional and observational study designs. You will critically use different research reporting standards to plan and disseminate the findings of clinical trials that involve patients or community-based participants. At the end of the course, you will have a grasp of key methods that underpin a robust, ethical and well managed clinical trial in either the health service or commercial sector.
HPDM173: Child and Adolescent Mental Health
This module outlines key concepts and evidence relating to child and adolescent ('young people's') mental health, paying particular attention to approaches relevant to public health. You will gain an understanding of a range of mental health challenges in childhood and adolescence, including population trends over time and the impacts of both good and poor mental-health during development on lifecourse trajectories. We will cover key areas of focus relevant to child and adolescent mental health, including epidemiology, factors that put a young person at risk of mental ill-health, mentally healthy systems and communities, and public health approaches to supporting, preventing and treating mental health problems.
Delivery will be a combination of recorded lectures and focussed examples, with self-directed learning tasks, as well as synchronous sessions to problem solve and consolidate knowledge.
HPDM193: Advanced Immunopathology
Our immune system has iteratively evolved into a highly regulated and sophisticated system that can identify and eliminate almost any microbe and aberrant self. An imbalance in this regulation can lead to unwanted immune responses causing a diverse range of immune-mediated pathologies, that affect increasing numbers of people and lead to societal burden. In Advanced Immunopathology you will gain in-depth knowledge of selected immune-mediated pathologies by critically appraising the related aetiology, pathophysiology (at molecular and cellular level) and exploring therapeutic approaches to modify unwanted immune response.
We would expect you to have an undergraduate background in a relevant biological subject. Such a background will provide the foundational knowledge needed to complete this course.
Study of the immune system and related immune-mediated pathologies is a fascinating, complex and fast-moving research field with great potential for clinical translation. Ongoing research provides us with an ever-clearer insight into the aetiology and pathophysiology. These advances allowed development of and research on therapies that target specific immune pathways to modulate unwanted immune responses.
PSYM223: Social Psychology
Social psychology seeks to understand how people think, feel and act in relation to others and the world around them. As such, the topics of interest to social psychologist cover much of what humans do, from personal choices to helping others and interactions in groups. Because social psychology is applicable to so many domains, it is also directly relevant to everyday life - by learning about social psychology, inevitably you also learn something about yourself.
This module is structured in two core activities, lectures and practicals/tutorials. The lectures will provide you with a good oversight of key topics in social psychology. Specific areas will be introduced in each lecture; we will identify why it is important,and discuss both classic studies in social psychology as well as new directions in this evolving and exciting field. Practicals/tutorials will be focused on giving you an understanding of research methodologies used in social psychology and their limitations as well as teaching you how to run basic social psychological analyses on a set of data. You will also learn to write about social psychological research. Learning will also be based on Question & Answer sessions.
PSYM227: Clinical Psychology
Clinical Psychology is a major area of Applied Psychology that makes a difference in people's lives by helping them deal with a range of problems. From depression and anxiety, psychosis and drug problems through to managing the effects of brain injury or the risk of heart attacks. The module involves the use of psychological theories - such as Psychodynamic or Cognitive Behavioural and the collection of evidence for 'what works' - to guide practice. In this module clinical psychologists give lectures that provide overviews to major mental health and neuro-developmental disorders, providing you with a valuable insight into how such problems arise, the treatments that may be offered and to what benefit. This module provides a key starting point for anyone considering a future in applied psychology enabling them to understand the true nature of the role.
To provide an overview of how clinical psychologists understand major psychological disorders from a bio-psycho-social perspective. The specific aims of the module are:
PSYM230: Advances in Clinical Psychology and Neuroscience
In this module you will explore the cutting edge of research in Clinical Neuroscience and Clinical Psychology. Across a range of topics, you will obtain a thorough understanding of both theoretical and practical approaches to understanding brain and behaviour relationships. You will learn how to use techniques developed for understanding brain functions, and how these may be used in the treatment of clinical populations to improve outcomes or by researchers working to understand clinical populations and therapeutic outcomes - both in neurological and mental health groups.
This module aims to develop a critical awareness of the broad range of methods available in clinical psychology and neuropsychology, using the pool of expertise at our disposal among the department's academic staff and associates. The module will enable you to sample and learn from a wide range of examples of historical and current research within these research areas. It aims to develop expertise in critical analysis and research design, and provide experience in the communication of ideas in a concise and engaging manner.
Through attending the weekly seminars, discussion and completing the assessments, you will further develop the following academic and professional skills:
Fees
2026/27 entry
UK fees per year:
£13,300 full-time 1 year
International fees per year:
£31,200 full-time 1 year
Scholarships
The University of Exeter offers a wide range of scholarships to support your education, with £7 million available for international students applying to study with us in the 2026/27 academic year, including our prestigious Exeter Excellence Scholarships. We also provide awards for sport, music and other achievements, as well as regional and partner scholarships with organisations such as Chevening, The Beacon Trust and the British Council. For more information on scholarships and other financial support, please visit our scholarships and bursaries page.
University of Exeter Alumni Scholarship
We are pleased to offer the University of Exeter Alumni Scholarship, a scholarship for University of Exeter alumni beginning a standalone postgraduate programme in 2026/27 with us a scholarship worth 20% of the cost of your first year tuition fees.
Terms and conditions, including deadlines, apply.
Teaching and research
Course structure
This campus-based programme is delivered primarily at Exeter’s St Luke’s Campus, with access to state-of-the-art neuroscience laboratories and dedicated computing facilities. Modules are designed to build progressively, with delivery coordinated to ensure a smooth learning experience.
Our Aim
We aim to provide transformative training at the intersection of neuroscience and data science, equipping you with the knowledge and technical expertise to investigate brain function, disease, and behaviour through cutting-edge research approaches.
Teaching
Learning takes place through a blended model, including lectures, seminars, coding workshops, practical sessions, and small-group tutorials. All teaching is supported by digital resources via the University’s electronic learning environment (ELE). You’ll be encouraged to share ideas, refine research skills, and apply new methods under the guidance of leading neuroscientists and data science specialists.
Research
A major element of the course is the independent research dissertation, where you’ll apply computational and experimental approaches to neuroscience data in collaboration with our expert research teams.
Learning
The programme combines structured teaching with guided independent study. You’ll gain technical, analytical, and ethical research skills, applying them to real-world challenges in neuroscience and data-driven discovery.
Assessment
Each module includes both formative and summative assessments. Formative tasks provide feedback and space to develop ideas, while summative assessments test your subject knowledge, data science proficiency, and transferable research capabilities.
Facilities
Based at Exeter’s St Luke’s Campus, you’ll benefit from:
- State-of-the-art neuroscience laboratories and specialist research equipment.
- Dedicated computing suites for programming, AI, and advanced data analysis.
- Access to extensive online journals and over 1.2 million e-books.
- A collaborative, interdisciplinary environment alongside experts in neuroscience, data science, and health research.
Careers
Who is this course for?
This MSc is designed for students who are passionate about exploring the brain and its disorders, whether their background is in neuroscience, psychology, life sciences, medicine, or a related discipline. It is ideal for those aiming to pursue a research career, move into the pharmaceutical, biotechnology, or healthcare sectors, or gain advanced analytical and technical skills valued across scientific and clinical fields. The programme also suits graduates seeking to develop expertise in data-driven neuroscience, preparing them for emerging roles in computational research, neuroimaging, and big data applications.
Employer-valued skills this course develops
Graduates of this MSc will develop a wide range of highly transferable, employer-valued skills. These include:
- Advanced data analysis skills, including programming, statistical modelling, and machine learning.
- Critical thinking and problem-solving abilities for addressing complex neurological challenges.
- Laboratory and research techniques for investigating brain function and disease.
- Project management, teamwork, and communication skills developed through collaborative research.
- The ability to translate scientific findings into practical applications across academia, industry, and healthcare.
Careers support
All University of Exeter students have access to Career Zone, which gives access to a wealth of business contacts, support and training as well as the opportunity to meet potential employers at our regular Careers Fairs. Our academic staff and practitioners will introduce you to relevant established professional networks.
