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Award details

Machine Learning Predictive Maintenance for Sustainable Urban Drainage. Engineering PhD Studentship (Funded) Ref: 4123

About the award



Exeter Academic Lead: Professor Gavin Tabor, College of Engineering, Mathematics and Physical Science, University of Exeter

Queensland Academic Lead: Professor Damien Batstone, Advanced Water Management Centre, The University of Queensland

Additional Supervisors: Professor Slobodan Djordjevic, College of Engineering, Mathematics and Physical Science, University of Exeter

Dr Daniel Jarman, Hydro International UK

Join a world-leading, cross-continental research team

The University of Exeter and the University of Queensland are seeking exceptional students to join a world-leading, cross-continental research team tackling major challenges facing the world’s population in global sustainability and wellbeing as part of the QUEX Institute. The joint PhD programme provides a fantastic opportunity for the most talented doctoral students to work closely with world-class research groups and benefit from the combined expertise and facilities offered at the two institutions, with a lead supervisor within each university. This prestigious programme provides full tuition fees, stipend, travel funds and research training support grants to the successful applicants.  The studentship provides funding for up to 42 months (3.5 years).

Eight generous, fully-funded studentships are available for the best applicants, four offered by the University of Exeter and four by the University of Queensland. This select group will spend at least one year at each University and will graduate with a joint degree from the University of Exeter and the University of Queensland.

Project Description

Waste water from urban and industrial sources has to be processed before being returned to the natural environment - this can involve removal of a wide range of pollutants both chemical, biological and particulate.  The importance of doing this has become increasingly apparent over the past decades, whilst the impact of changing climate in  the UK and Australia continues to generate increased stress on water infrastructure. Failure of our national wastewater infrastructure can result in risks to public health and the environment, and as systems become more complex, it is more difficult to detect point and diffuse failure.

Delivering resilient infrastructure systems has been identified as a key theme in the 2050 UK Water Innovation Strategy. Developing robust methods to understand asset health and predict how assets deteriorate is a targeted outcome of the strategy, which the project will help to fulfil.

In the last few years, Data Science methods have developed that promise to revolutionize almost every area of engineering. Given appropriate datasets, Machine Learning algorithms such as Neural Networks can be trained to recognise patterns in data which can be used as the basis for digital twin models of highly complex systems, at a level which is even now almost beyond what humans are capable of unaided. The aim of our project is to leverage these new technologies to develop a world-beating toolkit for predictive maintenance which can be applied to manage the thousands of water treatment assets which make up a typical regional  wastewater treatment infrastructure. To develop a failure model for any type of device requires access to historical data about events leading to failure. The project is being supported by the company Hydro International who are donating a database of maintenance records from over 1,200 process units maintained by Water and Sewerage Companies (WaSCs) throughout the UK. In Australia, Urban Utilities (SEQ wastewater operator) has been approached to provide a validation data set for application in the South East Queensland area

Further Information

Find out more about the PhD studentships

Successful applicants will have a strong academic background and track record to undertake research projects based in one of the three themes of:  Healthy Living, Global Environmental Futures and Digital Worlds and Disruptive Technologies.

The closing date for applications is midnight on 24 May 2021 (BST), with interviews taking place week commencing 12 July 2021. The start date is expected to be 10 January 2022.

Please note that of the eight Exeter led projects advertised, we expect that up to four studentships will be awarded to Exeter based students.


Entry requirements

Applicants should be highly motivated and have, or expect to obtain, either a first or upper-second class BA or BSc (or equivalent) in a relevant discipline.

If English is not your first language you will need to meet the English language requirements and provide proof of proficiency. Click here for more information and a list of acceptable alternative tests.

How to apply

You will be asked to submit some personal details and upload a full CV, supporting statement, academic transcripts and details of two academic referees. Your supporting statement should outline your academic interests, prior research experience and reasons for wishing to undertake this project, with particular reference to the collaborative nature of the partnership with the University of Queensland, and how this will enhance your training and research.

Applicants who are chosen for interview will be notified week commencing 28 June 2021, and must be available for interview week commencing 12 July 2021.

Please quote reference 4123 on your application and in any correspondence about this studentship.


Application deadline:24th May 2021
Value:Full tuition fees, stipend of £15,609 p.a, travel funds of up to £15,000, and RTSG of £10,715 are available over the 3.5 year studentship
Duration of award:per year
Contact: PGR Admissions Office