Job Description Job Summary
Applications are invited for a fully funded 24-month position at the Research Assistant / Associate level (informally known as “Post-doc”) within the Physics-aware Data Assimilation and Machine Learning Group (PI: Luca Magri) in the Department of Aeronautics at Imperial College London. The position is funded by the EPSRC ExCALIBUR project “Turbulence at the Exascale: Application to Wind Energy, Green Aviation, Air Quality and Net-zero Combustion”. The project is a collaboration led by Imperial College London together with the universities of Warwick, Cambridge, Newcastle, Southampton, and the Daresbury Laboratory. The post holder will develop physics-aware machine learning for the optimization of engineering systems with fluids. Funding is available for travelling and IT facilities for research-related tasks. The Research Associate is expected to produce results suitable for presentation in international conferences and publication in leading peer-reviewed journals/conferences.
The over-arching goal is to develop machine learning methods that are aware of the physics of the problem with a focus on exascale computing. Applications involve fluid mechanics. More information on the PI’s research can be found here: https://www.imperial.ac.uk/people/l.magri .Duties And Responsibilities
- Develop physics-aware machine learning methods for optimization of unsteady flows taking advantage of GPUs
- Disseminate research with peer-reviewed publications and conference presentations (with the PI)
- When ready and under the PI’s approval, publish the scientific results in journals and conferences
Experience in machine learning and/or data assimilation with experience in numerical methodsThose appointed at Research Associate level
PhD (or equivalent doctorate degree) in Engineering, Applied Mathematics, Computing, or a closely related discipline with experience in high performance computing, fluid mechanics and machine learning.Those appointed at Research Assistant level
Hold a Master degree or near completion of a PhD (or equivalent) in Computer Science, Engineering, Applied Mathematics, Computing, or a closely related discipline.
- Candidates who have not yet been officially awarded their PhD will be appointed as Research Assistant.
Should you require any further details on the role please contact: Luca Magri, email@example.com
For queries regarding the recruitment process please contact Lisa Kelly: firstname.lastname@example.org
The College is a proud signatory to the San-Francisco Declaration on Research Assessment (DORA), which means that in hiring and promotion decisions, we evaluate applicants on the quality of their work, not the journal impact factor where it is published. For more information, see https://www.imperial.ac.uk/research-and-innovation/about-imperial-research/research-evaluation/
The College believes that the use of animals in research is vital to improve human and animal health and welfare. Animals may only be used in research programmes where their use is shown to be necessary for developing new treatments and making medical advances. Imperial is committed to ensuring that, in cases where this research is deemed essential, all animals in the College’s care are treated with full respect, and that all staff involved with this work show due consideration at every level. http://www.imperial.ac.uk/research-and-innovation/about-imperial-research/research-integrity/animal-research /
Imperial College is committed to equality of opportunity, to eliminating discrimination and to creating an inclusive working environment. We are an Athena SWAN Silver award winner, a Stonewall Diversity Champion, a Disability Confident Employer and work in partnership with GIRES to promote respect for trans people.