Research Fellow in Fluid Mechanics- University of Leeds

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Location: Leeds
Job Description:

Overview

Research Fellow in Fluid Mechanics- University of Leeds

We are looking for a Research Fellow to join our project, working on designing, implementing and analysing algorithms to perform Direct Statistical Simulation of fluids (and potentially plasmas) in laboratory, geophysical and astrophysical settings, and comparing these with the statistics derived from Direct Numerical Simulation, where appropriate. The project (funded by the award of a European Research Council Advanced Grant) will involve the mathematical evaluation of statistical approximations, the development of computationally efficient algorithms for parallel architectures and the analysis of the effectiveness of the procedure. You will work closely with the Principal Investigator (PI) Professor Steve Tobias in the Department of Applied Mathematics, and with the Co-Investigator Professor Brad Marston in the Department of Physics at Brown University.

To explore the post further or for any queries you may have, please contact: Professor Steven Tobias, Professor of Applied Mathematics

Faculty/Service: Faculty of Mathematics & Physical Sciences

School/Institute: School of Mathematics

Category: Research

Grade: Grade 7

Working Time: 37.5 hours per week

Post Type: Full Time

ContractType: Fixed Term (3 years with the possibility of an additional two years – due to external funding)

Responsibilities

  • Design, implement and analyse algorithms to perform Direct Statistical Simulation of fluids (and potentially plasmas) in laboratory, geophysical and astrophysical settings.
  • Compare Direct Statistical Simulation results with statistics derived from Direct Numerical Simulation where appropriate.
  • Mathematically evaluate statistical approximations and develop computationally efficient algorithms for parallel architectures.
  • Analyse the effectiveness of the procedures and work closely with the Principal Investigator and Co-Investigator.

Qualifications

  • PhD in Applied Mathematics, Physics or a closely allied discipline.
  • Strong background in Fluid Dynamics and experience designing, implementing and analysing algorithms for fluid problems on parallel architectures.
  • Ability to conduct independent research and a developing track record of publications in international journals.
  • Excellent communication, planning and team working skills.

How to apply / Contact

For inquiries, please contact Professor Steven Tobias, Professor of Applied Mathematics.

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Posted: June 1st, 2026