Research Assistant/ Associate in Physics-Aware Machine Learning for Wind Farm Optimisation
Applications are invited for the role of Research Assistant / Associate in physics-aware machine learning for wind farm optimisation. This is a fully-funded post 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...
Job listing information
- Reference ENG02610
- Date posted 28 April 2023
- Closing date 28 May 2023
Applications are invited for the role of Research Assistant / Associate in physics-aware machine learning for wind farm optimisation. This is a fully-funded post 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 physics-aware machine learning for the optimisation of wind farm (layout optimisation and maximisation of power). The position involves computational fluid dynamics, high performance computing and a good understanding of turbulent flows. You will also contribute to maintaining and developing the wind farm simulator Winc3d which is part of the Xcompact3d framework of solvers based on finite-difference methods.
Duties and responsibilities
- Develop physics-aware machine learning methods for optimisation of wind farms taking advantage of GPUs
- Develop physics-aware machine learning methods for optimisation of unsteady flows.
- Contribute to adding new capabilities to the Xcompact3d framework.
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.
- Practical experience within a research environment and/or publication in relevant and refereed journals.
- Broad range of techniques including fluid mechanics, data-driven methods, programming and high performance computing.
- Knowledge of fluid mechanics and optimisation.
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: Prof Sylvain Laizet firstname.lastname@example.org
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