PhD in Computational

Start Date: As soon as possible/nClimate change and the race to decarbonize our society is making extreme events in fluids more prevalent. These are rare events where the flow suddenly takes extreme states far from its normal state. 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./nIn this project, you will develop machine learning-based reduced-order models which can accurately forecast these extreme events across a series of complex flows. This will entail performing high-fidelity simulations of a range of flows exhibiting extreme events, developing hybrid physics-based/machine learning modelling techniques and the embedding of such models within data assimilation frameworks to enable their self-correction./nDuring this project, you will develop expertise in machine learning-based reduced-order modelling and high-fidelity simulations of turbulent reacting flows. You will have the opportunity of using cutting-edge facilities such as Imperial College HPC facilities./nYou will have access to engaging professional development workshops in areas such as research communication, computing and data science, and professional progression through our Early Career Researcher Institute.