Project description
Starting date: 01 October 2026
This PhD offers an exciting opportunity to explore reservoir computing, a new approach towards artificial intelligence that uses the natural dynamic behaviour of physical systems (such as light and electronics) to process information efficiently.
You will work at the intersection of mathematics, physics, electrical engineering and AI, helping to develop a theory that explains how and why these systems work — and how to design better ones.
Modern AI computing systems require large amounts of energy and computational power. Reservoir computing offers a promising alternative by using complex physical systems to perform tasks such as prediction, classification, and signal processing.
However, one major challenge remains: We still do not fully understand what makes a reservoir computing system perform well. This PhD project aims to answer this question.
You will develop a unified mathematical theory and framework to study and explain how different reservoir systems work and how to design them for specific tasks. The project will combine:
- Mathematical modelling of dynamical systems;
- Computational photonics simulations;
- Comparison with real physical systems (especially photonic systems using light).
Funding and eligibility
The project is fully funded by DSTL, due to funding requirement this studentship is only available for UK (home) candidates.
An UKRI rate studentship is available for this project, covering home tuition fees plus a tax-free stipend.
How to apply
Send the following documents to sendy.phang@nottingham.ac.uk
- CV
- Cover letter explaining your research interests, relevant skills and experience, and why you are interested in this PhD project
- Academic transcripts (for both undergraduate and postgraduate degrees, if applicable)
- Copies of any publications (if applicable)
Please use “PhD-RC-Framework application – [Your Full Name]” as email subject matter.
Shortlisted candidates will be invited for an interview to assess their suitability.
Application deadline: 01 June 2026
Supervisors:
Professor Gregor Tanner – School of Mathematical Sciences, gregor.tanner@nottingham.ac.uk
Dr Sendy Phang – Faculty of Engineering, sendy.phang@nottingham.ac.uk