Research Assistant or Associate in Computational and Machine Learning Tools for Extreme Events in Engineering Fluid Flows
This post (Research Assistant/Associate in Computational and Machine Learning Tools for Extreme Events in Engineering Fluid Flows) is dedicated to developing hybrid simulation/machine learning tools for the prediction and control of extreme events in engineering-relevant flows.
These are rare events where the flow suddenly takes extreme states far from its normal state. These extreme events are becoming increasingly important as, the next generation of sustainable engineering flow systems will need to operate in more extreme environments or could themselves exhibit extreme behaviours. Of particulars risks are potential extreme events involving carbon-free fuels in future sustainable propulsion systems such as flashback which can occur with hydrogen or blow-off with ammonia.
What you would be doing
You will develop computational methods for the forecasting and control of extreme events in turbulent (reacting) flows. This will include interfacing high fidelity simulation codes with machine learning libraries and deploying them on high-performance computing centres. You will develop and apply this hybrid framework on engineering-relevant flows such as flashback in hydrogen reacting flows.
What you would be doing:
You will develop computational methods for the forecasting and control of extreme events in turbulent (reacting) flows. This will include interfacing high fidelity simulation codes with machine learning libraries and deploying them on high-performance computing centres. You will develop and apply this hybrid framework on engineering-relevant flows such as flashback in hydrogen reacting flows.
What we are looking for
Research Associate: Hold a PhD in Aerospace Engineering, Atmospheric Physics or a closely related discipline, or equivalent research, industrial or commercial experience
Research Assistant: A first / masters degree (or equivalent) in Aerospace Engineering, Atmospheric Physics, or a closely related discipline
*Candidates who have not yet been officially awarded their PhD will be appointed as Research Assistant.
- You should hold, or be close to completing, a PhD in Aerospace/Mechanical Engineering, Physics, Computer Science, Applied Mathematics, or a related field.
- Strong background in one or more of the following areas: high-fidelity CFD, high-performance computing, machine learning, fluid mechanics, or related fields.
- Prior experience in reacting flow is highly desirable but not essential
What we can offer you
- Integration in a wider team working on extreme events in fluids under the European Research Council project CONTEXT
- A highly flexible role in which you will have the opportunity to collaboratively identify and define your research objectives.
- The opportunity to gain supervision and project management experience.
- Ample scope for travelling to international conferences to disseminate the work done.
- Ample scope for publishing in leading journals.
- The opportunity to continue your career at a world-leading institution and be part of our mission to continue science for humanity.
- Sector-leading salary and remuneration package (including 39 days off a year and generous pension schemes).
Further information
This position is available until 31 March 2030.
*If you require any further details on the role please contact: Anh Khoa Doan (n.doan@imperial.ac.uk).
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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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.
We reserve the right to close the advert before the stated closing date, should we receive a high volume of applications.
If you have any general queries about this vacancy, please contact the hiring manager listed in the ‘Further Information’ section. Alternatively, you can contact the Recruitment Hub at recruitmenthub@imperial.ac.uk, and we will be happy to assist you.
If you experience any technical issues that prevent you from submitting an application, please contact our Technical Support team at support.jobs@imperial.ac.uk , who will be able to help resolve the issue.
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Research Assistant or Associate in Computational and Machine Learning Tools for Extreme Events in Engineering Fluid Flows employer: Imperial College London
Imperial College London is an exceptional employer, offering a vibrant work culture that fosters collaboration and innovation within the International Relations Office. Employees benefit from professional growth opportunities, a commitment to diversity, and the chance to engage in meaningful projects that have a global impact, all set in the heart of one of the world's leading academic institutions.