PhD Studentship – Prediction of Extreme Events in Turbulent Reacting Flows with Scientific Machine Learning
Imperial College London
London, United Kingdom
This stimulating fully funded PhD studentship at Imperial College London’s Department of Aeronautics offers an opportunity for an early-career researcher to contribute to cutting-edge research at the interface of fluid dynamics, reacting flows, and scientific machine learning. The project, supervised by experienced faculty within a world-class aeronautics research environment, focuses on advancing methods to predict extreme events in turbulent reacting flows by integrating data-driven modelling with advanced computational techniques. Turbulent reacting flows are ubiquitous in natural and engineered systems — from combustion processes in aerospace propulsion to atmospheric phenomena — and capturing their intermittent and extreme behaviour remains a grand challenge in fluid mechanics and machine learning. Through this studentship, successful candidates will engage with novel simulation frameworks and develop machine-learning-enhanced predictive tools that deepen understanding of complex flow physics while pushing the frontiers of computational research.
Eligibility Criteria
Applicants should hold, or be expected to complete, a first-class honours degree (such as MEng, MSci or equivalent) in Aeronautical Engineering, Mechanical Engineering, Applied Mathematics, Physics, Computational Science, or closely related STEM disciplines. A strong academic background that demonstrates aptitude for rigorous quantitative research is expected.
Required Expertise, Skills
Candidates will benefit from experience in or a strong interest in research-level scientific machine learning, computational fluid dynamics, and turbulence modelling. Familiarity with numerical simulation tools and programming languages commonly used in computational science (such as Python, MATLAB, or C++) will support success in this interdisciplinary project. The role will cultivate advanced analytical, modelling, and simulation skills.
Salary Details
This studentship covers full tuition fees and offers an annual tax-free stipend at the standard UKRI rate (typically around £22,780 for Home, EU and International students), supporting the researcher throughout the duration of the programme.
Application Deadline
The closing date for applications is 1 April 2026.