Neuron activity waves in brain cortex: reinforcement learning to optimise Brain productivity (Ref: PH/SS-SF1/2026)

About the Project

It is well established that neural activity waves propagate across the cerebral cortex. However, it remains an open question how these waves contribute to brain computation and human intelligence. Existing mathematical frameworks for modelling neural activity are not well suited to describing neural waves. Recently, we proposed a new theoretical framework for cortical neural waves that makes it possible to analyse their computational potential, characterise information propagation in the brain, and explain a wide range of experimental observations within a unified wave-based concept—phenomena that were previously attributed to unrelated mechanisms (Science Advances 8, 2022, DOI: 10.1126/sciadv.abl5865). Similar ideas have also been applied to wave-based reservoir computing (Nature Communications 14, 8296, 2023, DOI: 10.1038/s41467-023-43891-y), opening a new research direction in wave-reservoir computing.

A major challenge in advancing both our understanding of cortical waves and the development of wave-based neuromorphic computation lies in the large number of parameters required to model these systems. In this project, the PhD student will apply state-of-the-art AI optimisation algorithms to identify optimal synaptic and wave configurations needed to realise specific brain functions or to enhance the performance of wave-based reservoir computing architectures.

The project will be carried out in collaboration with an international team of researchers across North America, Europe, and Asia, providing the student with a unique opportunity to engage with world-leading experts and develop a truly global research profile.

Name of primary supervisor/CDT lead:
Sergey Saveliev S.Saveliev@lboro.ac.uk

Entry requirements:
Applicants are expected to have achieved at least a 2.1 degree, or an equivalent qualification, in Physics, Mathematics, or Neuroscience.

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: 1st July 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 should be made online. Under programme name, select Physics. Please quote the advertised reference number: PH/SS-SF1/2026 in your application.
To avoid delays in processing your application, please ensure that you submit a CV and the minimum supporting documents.
The following selection criteria will be used by academic schools to help them make a decision on your application. Please note that this criteria is used for both funded and selffunded projects.
Please note, applications for this project are considered on an ongoing basis once submitted and the project may be withdrawn prior to the application deadline, if a suitable candidate is chosen for the project.
During the in-person or online interview, the panel will assess the applicant’s knowledge of modelling complex phenomena, as well as their understanding of a broad range of physics and mathematical concepts. Applicants are typically asked to give a short presentation on their previous research, followed by questions designed to evaluate their competencies inPhysics, Mathematics, Neuroscience and Computer Science.

Project search terms:
applied mathematics, artificial intelligence, computational mathematics, data science, physics, theoretical physics