Research Associate in AI Turbomachinery Design

Research Associate in AI for Turbo machinery Design

The Sustainable Energy Technology and Turbo machinery Laboratory (SETTL) at Imperial College London is seeking a postdoctoral researcher to contribute to a Mitsubishi Heavy Industries (MHI)-funded project focused on the application of artificial intelligence (AI) to turbo machinery design.

The project aims to investigate and demonstrate how AI can accelerate engineering design processes, enable more efficient exploration of complex design spaces, and unlock new opportunities for innovation in turbo machinery design for future energy and transportation systems. Working closely with industrial stakeholders, the successful candidate will further develop, validate and apply AI-enabled design methodologies integrated with computational fluid dynamics (CFD) to support the generation, evaluation, and optimisation of turbo machinery components.

The research outcomes will advance AI-enabled approaches to engineering design and support the development of more efficient and sustainable turbo machinery technologies.

This is an exciting opportunity to contribute to research at the intersection of AI, machine learning, CFD and turbo machinery, working with academic and industrial collaborators to develop innovative approaches to engineering design. The postholder will work with Dr Teng Cao in the Thermofluids Division of the Department of Mechanical Engineering.

• Undertake research in AI-enabled turbo machinery design, CFD and machine learning.
• Develop and apply machine learning-based design frameworks for turbo machinery applications.
• Conduct numerical simulations and analyse turbo machinery performance.
• Prepare and process data for machine learning and CFD workflows.
• Contribute to project reports, publications and presentations.
• Engage with the industrial sponsor and participate in project meetings.

• You should hold, or be close to completing, a PhD in a relevant discipline (such as Mechanical Engineering, Aerospace Engineering, Physics, Computer Science, Applied Mathematics, or a related field).
• You should have a strong background in one or more of the following areas: machine learning, CFD, turbo machinery, and fluid dynamics.
• You should have track record of high-quality research publications in fluid mechanics, turbo machinery, machine learning, CFD, or related fields.
• You should have strong communication and interpersonal skills, with the ability to work effectively in both academic and industrial research environments.

• Working as part of a diverse, friendly, and supportive departmental team.
• Opportunity to work and network with a wide variety of College and Faculty teams.
• The opportunity to continue your career at a world-leading institution
• Sector-leading salary and remuneration package (including 43 days off a year)

This position is fixed term and is expected to run until 31 st October 2027.

We anticipate that the successful candidate will start on 1 st November 2026.

Hybrid working may be considered for this role. Staff working in roles that are suitable for hybrid working will normally be expected to work 60% of their time onsite. The opportunity for hybrid working will be discussed at interview.

Attached documents are available under links. Clicking a document link will initialize its download.

Please note that job descriptions are not exhaustive, and you may be asked to take on additional duties that align with the key responsibilities mentioned above.

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