Learning the dynamics of turbulence to inform practical fluids' modelling (Ref: ABCE-SECC-CK)

About the Project

Turbulence is the great unsolved problem in classical physics yet modelling turbulence appropriately is vital for effective engineering design of aircraft, wind turbines and combustion processes and for understanding our evolving environment. This project will make use of recent theoretical developments and results from our own work to consider how to construct the next generation of practical engineering closures for turbulent flows. The pathway to the future looks to be a stochastic differential equation approach but how best to formulate this given the nonlocal and nonlinear properties of turbulent flows is an open problem. This project will involve looking at the equations afresh and then using machine learning methods to constrain the search of the relevant parameter space to develop a new modelling approach.

Name of primary supervisor/CDT lead:
Chris Keylock c.j.keylock@lboro.ac.uk

Name of secondary supervisor:
Jialin Su

Entry requirements:
Applicants should have, or expect to achieve, at least a 2:1 honours degree (or equivalent) in a relevant subject such as Mathematics, Physics, Statistics or Computational Engineering. A relevant master’s degree and/or experience is desirable

English language requirements:
Applicants must meet the minimum English language requirements. Further details are available on the International website (http://www.lboro.ac.uk/international/applicants/english/).

Bench fees required: No

Closing date of advert: 30th June 2026

Start date: October 2026

Full-time/part-time availability: Full-time 3 years

Fee band: 2025/26 Band RB (UK £5,006, International £28,600)

How to apply:
All applications must be made online and must include a completed studentship application form (instead of a personal statement) and a two-page research proposal based on the project description outlining how you would approach the project and what methods you would use. Under programme name, please select 'Architecture, Building and Civil Engineering'. Please quote advert reference ABCE-SECC-CK.
To avoid delays in processing your application, please ensure that you submit the minimum supporting documents including an up-to-date CV, but a personal statement is not required.
ABCE will use these selection criteria to make a decision on your application.

Project search terms:
aerospace engineering, applied mathematics, computational mathematics, computational physics, fluid mechanics, machine learning, mathematical modelling, stochastic processes, turbulence, network science

Email Address ABCE:
abce.pgr@mailbox.lboro.ac.uk