About The Role

UE07: £41,064 - £48,822 per annum
CSE / School of Mathematics
Full time: 35 hours per week
Fixed-term: 36 months
Vacancies available: 2

The Opportunity

This project seeks to realise a new approach to turbulence computation via a combination of modern AI technology (graph neural networks and transformers) with a dynamical systems framework. The dynamical systems viewpoint imagines the turbulence as a space-time tapestry of connected states, which are related to exact solutions of the governing equations in smaller domains. This viewpoint is compelling: it connects dynamical events to statistical properties of the flow, it generates a set of rules by which different recurrent patterns can coexist and interact and it is a robust platform on which to build low-order models for deployment in industrial applications. However, to date this approach has been restricted to small-scale flows because of (1) the computational challenge of identifying the coherent patterns and (2) the combinatorial challenge of identifying the rules by which the patterns join to form the space-time tapestry. These problems are a natural fit for frontier AI models. The two postdocs on this project will, together with the PI, his collaborators and industrial partners, design, train and release these models.

These positions are funded by UKRI to work with Dr Jacob Page on the design and construction of large neural networks for the embedding and prediction of high Reynolds number turbulence. The approach is motivated by Hopf’s “dynamical systems” view of turbulent flows. The project includes collaboration with a leading researcher at a major tech company, in addition to ongoing collaborations with Prof Steve Brunton’s group at the University of Washington and Dr Georgios Rigas’ group at Imperial College London. There will also be scope for involvement in other ongoing industrial collaborations.

This post is full-time (35 hours per week).

View the full job description

How to apply

Please include the following documents in your application

CV
Research statement, including details as to how this project helps your career trajectory
Contact details of two academic references
References will be sought from shortlisted candidates

As a valued member of our team, you can expect

A competitive salary.
An exciting, positive, creative, challenging and rewarding place to work.
To be part of a diverse and vibrant international community.
Comprehensive Staff Benefits, including generous annual leave entitlement, a defined benefits pension scheme, a wide range of staff discounts, family-friendly initiatives, and flexible work options. Check out the full list on our staff benefits page (opens in a new tab) and use our reward calculator to discover the value of your pay and benefits.

Championing equality, diversity, and inclusion

The University of Edinburgh holds a Silver Athena SWAN award in recognition of our commitment to advance gender equality in higher education. We are members of the Race Equality Charter, and we are also a Stonewall Proud Employer, actively promoting LGBTQ+ equality.

We welcome applications from all qualified candidates and particularly encourage applications from women and other under-represented groups in applied mathematics.

Prior to any employment commencing with the University, you will be required to evidence your right to work in the UK. Further information is available on our right to work webpages webpages (opens new browser tab)

The University may be able to sponsor the employment of international workers in this role. This will depend on a number of factors specific to the successful applicant.

Key dates to note

The closing date for applications is 18 September 2026.

The positions begin on 1st October 2026 or as soon as possible thereafter.

Unless stated otherwise the closing time for applications is 11:59pm UK time. If you are applying outside the UK the closing time on our adverts automatically adjusts to your browsers local time zone.

Interviews will be held in late September.