Research Associate in AI for Turbomachinery Design

SONICOM; Greater London; Hybrid; GBP 42,000 - 56,000; Full time

Benefits offered by this job

43 days annual leave

Hybrid work option

Job summary

Imperial College London is seeking a Research Associate to contribute to an MHI-funded project applying artificial intelligence to turbomachinery design. The role focuses on AI-enabled design methods, CFD integration, and data-driven performance analysis in close collaboration with Dr.

Teng Cao and the Thermofluids Division. The successful candidate will conduct numerical simulations, develop ML-based design frameworks, and engage with industrial stakeholders to advance AI-enabled engineering

Qualifications

• PhD in Mechanical Engineering, Aerospace Engineering, Physics, Computer Science, Applied Mathematics or related field.
• Strong background in machine learning, CFD, turbomachinery and fluid dynamics.
• Track record of high-quality research publications in relevant fields.
• Strong communication and collaboration skills for academia and industry.

Responsibilities

• Undertake research in AI-enabled turbomachinery design, CFD and machine learning.
• Develop and apply machine learning-based design frameworks for turbomachinery.
• Conduct numerical simulations and analyse turbomachinery 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.

Skills

Machine learning

CFD

Turbomachinery

Fluid dynamics

Education

PhD

Job description

Research Associate in AI for Turbomachinery Design

The Sustainable Energy Technology and Turbomachinery 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 turbomachinery design.

The project aims to investigate and demonstrate how AI canaccelerate engineering design processes, enable more efficient exploration of complex design spaces, and unlock new opportunities for innovation in turbomachinery 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 turbomachinery components. The research outcomes will advance AI-enabled approaches to engineering design and support the development of more efficient and sustainable turbomachinery technologies.

This is an exciting opportunity to contribute to research at the intersection of AI, machine learning, CFD and turbomachinery, 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.

What you would be doing

• Undertake research in AI-enabled turbomachinery design, CFD and machine learning.
• Develop and apply machine learning-based design frameworks for turbomachinery applications.
• Conduct numerical simulations and analyse turbomachinery 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.

What we are looking for

• 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, turbomachinery, and fluid dynamics.
• You should have track record of high-quality research publications in fluid mechanics, turbomachinery, 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.

What we can offer you

• 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)

Further information

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.

About Imperial

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Join us and be part of something bigger. From global health to climate change, AI to business leadership, here at Imperial we navigate some of the world’s toughest challenges. Whatever your role, your contribution will have a lasting impact.

As a member of our vibrant community of 22,000 students and 8,000 staff, you’ll collaborate with passionate minds across nine London campuses and a global network.

This is your chance to help shape the future. We hope you’ll join us at Imperial College London.

Our Culture

We work towards equality of opportunity, to eliminating discrimination, and to creating an inclusive working environment for all. We encourage applications from all backgrounds, communities and industries, and are committed to employing a team that has diverse skills, experiences and abilities. You can read more about our commitment on your web pages .

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