This PhD program is designed for students interested in the intersection of neurobiologically inspired machine learning and computational neuroscience. You will join a vibrant research environment at the University of Sussex, contributing to multidisciplinary approaches to AI and brain function. The program offers two main research directions: developing more efficient deep learning models based on biological neural circuits, and exploring how agents learn continuously in changing environments, drawing inspiration from brain mechanisms. This PhD is ideal for individuals with a strong programming and mathematical background, and a passion for understanding intelligence in both biological and artificial systems.
English language qualifications should ideally have been achieved within two years before the course start date. Scores from different test sittings cannot be combined.
The studentship covers both tuition fees and provides a living stipend.
You need an undergraduate degree with at least a 2:1 honours classification in a relevant field like Computer Science, Mathematics, Neuroscience, or Psychology, demonstrating strong mathematical and computational modelling experience. You must also meet the University of Sussex's English language requirements, for example, an IELTS score of 6.0 overall with at least 6.0 in each component.
Yes, this PhD studentship covers all tuition fees for both UK and international students. It also provides an annual, tax-free living stipend of £21,805.
The program is designed to be completed within 3.5 years.
First, contact James.Bennett@sussex.ac.uk with your CV and a research statement. Then, submit a full online PhD application for Informatics via the University of Sussex portal, including a research proposal, CV, transcripts, and references.
The application deadline for this PhD studentship is 23:45 on June 12, 2026.
Graduates are well-prepared for research and development roles in academia or industry, particularly in areas such as AI research labs, tech companies focused on advanced algorithms, or scientific research institutions.