Research Fellow in Fluid Dynamics

Are you an ambitious researcher looking for your next challenge? Do you have an established background in computational methods and/or fluid dynamics? Do you want to further your career in one of the UK’s leading research-intensive universities?

We are looking for a Research Fellow to join our project, working on performing Direct Statistical Simulation (DSS) of partial differential equations (PDEs) and Machine Learning for turbulent flows. The project, which combines several new areas in statistics, PDEs and automated computational science, is funded by an award of a targeted grant from the Simons Foundation. The project is funded as part of the project “Revisiting the turbulence problem using statistical mechanics”. 

You will work with Investigator Professor Steven Tobias and his Co-Investigators to conduct research into the interaction of inhomogeneous and anisotopic turbulent flows with mean flows. The aim of the project is to understand factors that contribute to transition to turbulence and the generation of mean flows in geophysical and astrophysical contexts. As part of this, you will learn different mathematical and computational techniques, and apply them to diverse physical applications.

You will have a PhD in Applied Mathematics, Physics, Engineering or a closely allied discipline, with a strong background in Fluid Dynamics and experience in designing, implementing and analysing algorithms for fluid problems on parallel architectures. An understanding of statistical mechanics may also be useful. You will have the ability to conduct independent research and a developing track record of publications in international journals. In addition, you will have excellent communication, planning and team working skills. 

To explore the post further or for any queries you may have, please contact: 

Professor Steven Tobias, Professor of Applied Mathematics

Tel: +44 (0)113 343 5172 or email: S.M.Tobias@leeds.ac.uk

https://jobs.leeds.ac.uk/Vacancy.aspx?ref=EPSMA1023