Applications are invited for a fully-funded Industrial Doctoral Landscape Award, offered in partnership with Rolls-Royce, to tackle key challenges in the design of aeroengine oil systems using multiphase Computational Fluid Dynamics (CFD). This is an exciting opportunity to contribute to cutting-edge research that supports the next generation of  sustainable aeroengines.

The successful candidate will join a supportive team of 50 researchers, technicians and academics within the Mechanical and Aerospace Systems Research Group, and will have the opportunity to apply their research during a placement within Rolls Royce.

Project Overview

The project focuses on developing and applying advanced CFD models for aeroengine oil systems. There will also be opportunities to integrate machine learning techniques for building lower-order predictive models. The student will gain hands-on experience in industrial applications, including practical aspects of aeroengine oil system design, spending part of their PhD based on-site at Rolls-Royce as well as receiving joint supervision and training from both the University and industry professionals.

Candidate Requirements

We are seeking an enthusiastic, self-motivated researcher with a rigorous approach to problem-solving. Applicants should have, or be expected to gain, a high 2:1 (preferably 1st class) honours degree in Mechanical or Aerospace Engineering, or a related discipline with substantial background in fluid mechanics.

Essential skills:

• Strong knowledge of numerical methods
• Ability to work effectively in a team

Desirable skills / experience:

• Experience of applying CFD to a complex problem
• Knowledge of multiphase flows
• Experience with machine learning techniques

Funding

This studentship covers UK home tuition fees and provides a tax-free stipend of up to £25,000 per year for 4 years. Please note that, due to funding restrictions, this studentship is only available to UK (home fees) citizens.

Start date – 1 October 2026

Application Process

Informal enquiries may be addressed to:
Dr Stephen Ambrose – Stephen.Ambrose3@nottingham.ac.uk  or

Dr Chris Ellis – Chris.Ellis@nottingham.ac.uk

Interested candidates should submit the following documents:

• Curriculum Vitae (CV)
• Cover letter
• Academic transcripts

Applications should be sent to IAT@nottingham.ac.uk

Candidates will be interviewed at the earliest possible convenience, and the position will close once a suitable candidate is found