Research Associate Machine Learning and Data
3 weeks ago
We have an exciting opportunity to join a strong collaborative project between Imperial College and several EU partners, Demoquas, on the development of new UQ methods for Aircraft Engines.
The project will involve a close collaboration with Rolls-Royce in UK and all other partners. To enable the next generation of aircraft engines, electric or using hydrogen, requires new and efficient Uncertainty Quantification models able to handle complex simulations, with multifidelity and multiscale methods.
The post will require travel and close collaboration with other members of the project.
Take initiative in the planning of the research and collaboration under minor supervision.
# Analyse real CFD data for real aircraft engines.
# Publish in world-leading journals in the field and communicate your work at project meetings as well as externally at conferences and working group meetings.
Those appointed at Research Associate level:
Hold a PhD in Engineering, Turbomachinery, Machine Learning, UQ or CFD, or a closely related discipline, or equivalent research, industrial or commercial experience.
Those appointed at Research Assistant level:
A first / masters degree (or equivalent) in Engineering, Turbomachinery, Machine Learning or CFD, or equivalent research, industrial or commercial experience or a closely related discipline.
*Candidates who have not yet been officially awarded their PhD will be appointed as Research Assistant.
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