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PhD Studentship in Aeronautics: Machine Learning-based Control of Reacting Flow Extreme Events (AE0092) Imperial College London in United Kingdom
Degree Level
PhD
Field of study
Computer Science
Funding
Available
Deadline
Jan 4, 2027
Country
United Kingdom
University
Imperial College London
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About this position
This PhD studentship at Imperial College London sits in Aeronautics and focuses on machine learning-based control of reacting flow extreme events. The project addresses rare but potentially serious combustion-related events in future sustainable propulsion systems, including hydrogen and sustainable aviation fuels, where sudden transitions such as flashback and thermoacoustic instabilities can threaten safe operation.
The research aims to develop a framework that combines a differentiable reacting flow solver with a machine learning-based controller. The solver will provide short-term state dependence, which the controller can use to identify mitigation actions designed to prevent extreme events in reacting flows. The work is intended to span multiple reacting flow applications and to explore novel actuators such as spray water injection and electrically driven fuel droplet control.
You will join a research group working on the European project CONTEXT, at the intersection of scientific machine learning and fluid dynamics. The project offers close interaction with expertise across the department, including turbulence and machine learning specialists. The advert highlights the opportunity to work under the supervision of Dr. Nguyen Anh Khoa Doan and to engage with other researchers in the broader department.
The studentship emphasises hands-on development in reacting flow physics, machine learning for fluids and control, and high-fidelity simulation, with access to Imperial College HPC facilities. It also places the student in a research environment with professional development opportunities and the chance to participate in international conferences.
Funding details
Available
What's required
Candidates are expected to have achieved or be on track to achieve a First class honours MEng/MSci or higher degree, or an international equivalent, in Aeronautical/Mechanical Engineering, Applied Mathematics, Computer/Data Science, or Applied or Computational Physics. The advert particularly seeks students with experience in Fluid Mechanics, Turbulence, CFD, Machine Learning, and Reacting Flows.
How to apply
Visit the advertised project page for important instructions on how to apply. For admissions questions, check the FAQ first, then email the PhD Administrator (Admissions) if your question is not answered.
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ApplyKite TwinLearns as you applyMake your next move.
Prepare your application
Review drafts and confirm requirements with the provider.