Theme: Technology

Project Description

Could large-scale brain imaging help explain why people with the same mental health diagnosis can have very different symptoms? And could it support more personalised care?

This PhD will use neuroimaging and computational methods to study brain variation at population and clinical levels. It combines the scale of UK Biobank, with imaging from 100,000 participants, with detailed studies of psychosis, depression and anxiety, where MRI, neuropsychological assessments and clinical information are brought together.

A challenge is that MRI measurements vary across scanners, acquisition protocols and processing methods, making MRI features difficult to quantify and studies difficult to combine. You will develop and apply harmonisation methods, drawing on ON-Harmony and other resources, to make imaging features comparable. You will then build normative models from population-level data, creating reference patterns of brain variation against which individuals in clinical cohorts can be assessed. This approach will allow you to identify meaningful relationships between brain image patterns and mental health symptoms, discover patterns extending beyond conventional diagnoses, and evaluate imaging-derived measures for precision mental health research.

The project is designed for a healthcare professional who wants to bring clinical insight to data-driven research and further develop their computational expertise. Working with a multidisciplinary Nottingham-Oxford team, you will receive training in scientific programming, neuroimaging analytics, computational psychiatry and reproducible research. You will develop a distinctive combination of quantitative and clinical skills, preparing you for a clinical academic career and the opportunity to shape the future of personalised mental healthcare.