Events

Start Date: As soon as possible Application deadline: 1st April 2026 Introduction: Climate 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. Currently, we cannot accurately forecast such extreme events due to the chaotic nature of the underlying turbulent flows and the complex multiscale nonlinear interactions at the origin of such extreme events. In 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. During 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. You 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. Supervisors: You will join the growing team of researchers on the ERC project CONTEXT, working at the intersection of scientific machine learning and fluid dynamics, under the supervision of Anh Khoa Doan. You will also have the opportunity to interact with experts in turbulence and machine learning across the department, such as Prof. Luca Magri or Dr. Andrea Novoa. Duration: 3.5 years. Funding: Full coverage of tuition fees and an annual tax-free stipend of £22,780 for Home, EU and International students. Eligibility: You must possess (or expect to gain) a First class honours MEng/MSci or higher degree or equivalent in a Computational background: engineering, physics, maths, or computer science. How to apply: Submit your application via our Apply webpages: When submitting your application, you will need to use the following details: Search course/Programme: Aeronautics Research (PhD) Research Topic:Please use reference number AE0086 Research Supervisor: Dr Anh Khoa Doan Research Group:Aero For further information: For questions about the project, please contact: Dr. Anh Khoa Doan [email protected] For queries regarding the application process, please contact Lisa Kelly, PhD Administrator, [email protected] You can also learn more about Imperial at Equality, Diversity and Inclusion: Imperial is committed to equality and valuing diversity. We are an Athena SWAN Silver Award winner, a Stonewall Diversity Champion, a Disability Confident Employer and are working in partnership with GIRES to promote respect for trans people.