Solving Engineering Design Challenges through Computational Fluid Dynamics and Machine Learning - Engineering - ( EPSRC DTP funded PhD Studentship Ref: 2917

About the award

This project is one of a number funded by the Engineering and Physical Sciences Research Council (EPSRC) Doctoral Training Partnership to commence in September 2018. This project is in direct competition with others for funding; the projects which receive the best applicants will be awarded the funding.

The studentships will provide funding for a stipend which is currently £14,553 per annum for 2017-2018. It will provide research costs and UK/EU tuition fees at Research Council UK rates for 42 months (3.5 years) for full-time students, pro rata for part-time students.

Please note that of the total number of projects within the competition, up to 15 studentships will be filled.

Prof Gavin Tabor

Prof Jonathan Fieldsend 

Streatham Campus, Exeter

Project Description
Computational Fluid Dynamics (CFD) is the solution of complex fluid flow problems using computers. It is widely used in a range of industries to provide insight into the physical nature of the flow; which can then be used by engineers to improve their designs. It would be useful to be able to automate this design process, but there are significant challenges in doing so. Machine Learning (ML) is a branch of Computer Science which automates the construction of mathematical models of systems, allowing computers to find hidden insights without being explicitly programmed to do so. Coupling the two provides a powerful, cutting edge tool for engineers to use to identify and examine novel  solutions for key engineering problems. 

At Exeter we have developed a Machine Learning code based on the open source CFD code OpenFOAM, using a group of ML algorithms called Bayesian methods, which can be used to efficiently identify optimal solutions to complex (and computationally costly) problems. The objective of the PhD project will be to extend this and apply it to a number of important engineering problems. These will include applications in the automotive sector, such as optimising the shape of vehicle spoilers, and in pumps and turbines; developing the optimum shape for the turbine casing.

The position is fully funded as a PhD Scholarship award (EPSRC DTP) for 3.5 years including UK tuition fees and an annual maintenance allowance at current Research Council rate of £14,553 per year. EU awards are fees only. You will need to have a keen interest in participating in cutting edge research in machine learning and CFD, and have demonstrated exceptional ability in an Engineering or other area (at least a 2:1 degree in Engineering, Physics, Mathematics or Computer Science).

Entry Requirements
You should have or expect to achieve at least a 2:1 Honours degree, or equivalent, in Engineering, Physics or Mathematics. Experience in Computational Fluid Dynamics is desirable.

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.

The majority of the studentships are available for applicants who are ordinarily resident in the UK and are classed as UK/EU for tuition fee purposes.  If you have not resided in the UK for at least 3 years prior to the start of the studentship, you are not eligible for a maintenance allowance so you would need an alternative source of funding for living costs. To be eligible for fees-only funding you must be ordinarily resident in a member state of the EU.  For information on EPSRC residency criteria click here.

Applicants who are classed as International for tuition fee purposes are NOT eligible for funding. International students interested in studying at the University of Exeter should search our funding database for alternative options.


Application deadline:10th January 2018
Value:3.5 year studentship: UK/EU tuition fees and an annual maintenance allowance at current Research Council rate. Current rate of £14,553 per year.
Duration of award:per year
Contact: Doctoral

How to apply

You will be required to upload the following documents:
•       CV
•       Letter of application outlining your academic interests, prior research experience and reasons for wishing to
        undertake the project.
•       Transcript(s) giving full details of subjects studied and grades/marks obtained.  This should be an interim
        transcript if you are still studying.
•       If you are not a national of a majority English-speaking country you will need to submit evidence of your current
        proficiency in English.  For further details of the University’s English language requirements please see

The closing date for applications is midnight (GMT) on Wednesday 10 January 2018.  Interviews will be held at the University of Exeter in late February 2018.

If you have any general enquiries about the application process please email:
Project-specific queries should be directed to the supervisor.

During the application process, the University may need to make certain disclosures of your personal data to third parties to be able to administer your application, carry out interviews and select candidates.  These are not limited to, but may include disclosures to:

• the selection panel and/or management board or equivalent of the relevant programme, which is likely to include staff from one or more other HEIs;
• administrative staff at one or more other HEIs participating in the relevant programme.

Such disclosures will always be kept to the minimum amount of personal data required for the specific purpose. Your sensitive personal data (relating to disability and race/ethnicity) will not be disclosed without your explicit consent.