Research Assistant / Associate in Machine Learning of Road Vehicle Aerodynamics
Applications are invited the role of Research Assistant / Associate in Machine Learning of Road Vehicle Aerodynamics fully-funded until 31 March 2025. This position is funded by a UKRI AI for Net Zero grant. The over-arching goal is to develop machine learning methods that are aware of the physics of the problem for the realization of real-time digital twins of engineering systems. Applications involve fluid mechanics and nonlinear partial...
Job listing information
- Reference ENG02611
- Date posted 28 April 2023
- Closing date 28 May 2023
Applications are invited the role of Research Assistant / Associate in Machine Learning of Road Vehicle Aerodynamics fully-funded until 31 March 2025. This position is funded by a UKRI AI for Net Zero grant. The over-arching goal is to develop machine learning methods that are aware of the physics of the problem for the realization of real-time digital twins of engineering systems. Applications involve fluid mechanics and nonlinear partial differential equations.
You will develop and experimentally demonstrate machine learning flow control techniques for the optimisation of active road vehicle aerodynamics. Data-driven techniques (i.e. Real-Time Reinforcement Learning) will be employed to enable the discovery of optimal control algorithms of flow control devices and platooning formations directly from wind tunnel experiments in fully turbulent regimes. Funding is available for travelling and experiments in the flagship 10x5 National Wind Tunnel Facility at Imperial College.
Duties and responsibilities
- Develop and experimentally demonstrate real-time machine learning methods for optimisation of road vehicle aerodynamics including the design, set-up and undertaking of wind tunnel experiments.
- Develop physics-aware machine learning methods for optimisation of turbulent flows.
- Disseminate research with peer-reviewed publications and conference presentations (with the PI)
- PhD (or equivalent doctorate degree) in Engineering, Applied Mathematics, Computing, or a closely related discipline.
- Experience in a broad range of techniques including theoretical and experimental fluid mechanics, data-driven methods and programming
- Knowledge of programming, dynamical systems, fluid mechanics and optimisation as well as mathematical skills.
This post is a full time, fixed-term contract until 31 March 2025.
Candidates who have not yet been officially awarded their PhD will be appointed as a Research Assistant within the salary range £38,194 - £41,388 per annum.
Should you require any further details on the role please contact: Dr Georgios Rigas email@example.com
For queries regarding the recruitment process please contact Lisa Kelly: firstname.lastname@example.org
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Please note that job descriptions cannot be exhaustive, and the post-holder may be required to undertake other duties, which are broadly in line with the above key responsibilities.
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