Postdoctoral Research Associate in the Mathematical and Computational Foundations of Artificial Inte

University of Oxford; Oxford; On-site; GBP 41,000 - 48,000; Full time

Job summary

A prestigious research institution is seeking a Postdoctoral Research Associate to work on the EPSRC Hub focused on the Mathematical and Computational Foundations of Artificial Intelligence. This two-year fixed-term role involves conducting research, collaborating with other academics, and contributing to teaching. The ideal candidate will have a PhD in a relevant field along with experience in machine learning and mathematical optimisation. Salary ranges from £41,636 to £47,779 p.a. Applications are due by 12:00 noon on January 9, 2026.

Benefits

Athena SWAN Silver Award

Race Equality Charter Bronze Award

Qualifications

• PhD in a relevant field required.
• Experience in machine learning and mathematical optimisation.
• Ability to work collaboratively in a research environment.

Responsibilities

• Conduct research within the chosen theme(s) of the hub.
• Write up results for publication in refereed journals.
• Collaborate with other members of the hub and partners.

Skills

Manifold learning

Riemannian optimisation

Stochastic control

Education

PhD in a relevant field

Tools

Mathematical modelling

Machine learning frameworks

Job description

Postdoctoral Research Associate – EPSRC Hub AI

We invite applications for a Postdoctoral Research Associate (PDRA) to join the EPSRC Hub on the Mathematical and Computational Foundations of Artificial Intelligence. One PDRA will be recruited to work within one of, or across, the four research themes.

Research Themes

• Learning with Structured & Geometric Models: Apply tools from manifold learning and Riemannian optimisation to leverage underlying manifold structure for better training and novel network designs.
• Low Effective-dimensional Learning Models: Extend foundational theory of how large ML systems can be regularised to have dramatically fewer trainable parameters without sacrificing accuracy by analysing the use of low-dimensional building blocks.
• Implicit Regularization: Develop mathematical understanding of implicit regularisation properties in deep neural networks to guide the development of algorithmic paradigms aimed at combining statistical optimality with computational efficiency.
• Reinforcement Learning through Stochastic Control: Develop methods from stochastic control, providing a mathematically grounded approach with a well-posed continuous-time limit.

Position Details

• Two‑year fixed‑term position funded by a research grant from the EPSRC.
• Flexible start date.
• Salary: Grade 7 (£41,636 – £47,779 p.a.)

Responsibilities

• Conduct research within the chosen theme(s) of the hub.
• Collaborate with other members of the hub, both at Oxford and with partner universities, companies, and government organisations.
• Write up results for publication in refereed journals and proceedings, including co‑authored work.
• Contribute up to three hours a week of teaching during academic terms.

Benefits

• Departmental Athena SWAN Silver Award and institutional Race Equality Charter Bronze Award.

Application Procedure

Applications received before 12:00 noon UK time on Friday, 09 January 2026 will receive full consideration. Applicants must provide references directly to [e-mail] before the closing date. Please direct informal enquiries to the Recruitment Coordinator at [e-mail], quoting vacancy reference 183617.