Postdoctoral Research Associate

Posted 3 Days Ago
Be an Early Applicant
2 Locations
In-Office
41K-49K Annually
Entry level
Edtech • Information Technology • Professional Services
The Role
Conducts research on AI-enabled turbulence computation by designing, training, and releasing large neural network models for embedding and predicting high-Reynolds-number turbulent flows. The role applies graph neural networks, transformers, and dynamical systems theory, collaborating with academic researchers, industrial partners, and a major technology company. The position is full-time, fixed-term for 36 months, and includes opportunities for industrial collaboration and career development.
Summary Generated by Built In

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.

About UsAs a world-leading research-intensive University, we are here to address tomorrow’s greatest challenges. Between now and 2030 we will do that with a values-led approach to teaching, research and innovation, and through the strength of our relationships, both locally and globally. About the Team

The School of Mathematics

The University of Edinburgh's School of Mathematics is one of the world’s leading mathematical sciences departments, home to world-class researchers and to an innovative educational environment for both undergraduates and postgraduates. We are proud to have a highly international faculty and students from around the world.
As a School we value both the breadth and depth of our research and teaching.

We have around 110 permanent faculty and around 45 research fellows and research associates, who cover a broad range of research topics in pure and applied mathematics, operational research and statistics. The School has an enviable record of attracting prestigious fellowships and currently hosts, for instance, 6 ERC grant holders and 7 Royal Society University Research and Dorothy Hodgkin Fellows. In the 2023 Shanghai Global Ranking of Academic Subjects we are ranked 18th among the world’s best Mathematics departments.  Together with the Departments of Mathematics and Actuarial Mathematics & Statistics at Heriot-Watt University, we form the Maxwell Institute; our joint submission to REF2021was ranked 3rd in the UK for Mathematical Sciences by research power, based on the quality and breadth of our combined research.

The School delivers a world-leading educational experience for its students and is constantly exploring new evidence-based ideas in mathematical education in order to provide a stimulating learning environment. There are excellent possibilities for imaginative curriculum development, including online activities, and course design and delivery. The School teaches pure and applied Mathematics, operational research and statistics. We have approximately 1000 undergraduate students, around 210 MSc students, and our Graduate School has close to 160 PhD students.

Edinburgh is home to the International Centre for Mathematical Sciences, one of the UK’s two major conference centres in the mathematical sciences and operated jointly by the University with Heriot-Watt University. Over the past 30 years the centre has established a superb reputation for hosting workshops at the highest scientific level on all mathematical topics, attracting many of the best mathematicians in the world to the UK.

The School is located in the James Clerk Maxwell Building which is situated on the King's Buildings campus, approximately 3 kilometres south of the city centre. 

Further information about the School, our research and our teaching is available on the School of Mathematics Website (https://www.maths.ed.ac.uk) (Opens in new browser tab)

Skills Required

  • CV
  • Research statement explaining how the project supports the applicant's career trajectory
  • Contact details for two academic references
  • Evidence of the right to work in the UK before employment begins
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The Company
HQ: Edinburgh
12,606 Employees
Year Founded: 1583

What We Do

The University of Edinburgh Information Services Group is one of Scotland's largest information technology employers, specialising in a wide variety of IT jobs, EdTech services, and IT solutions. We provide library and digital services to the University of Edinburgh, a world leader in higher education teaching, research and innovation.

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