Multimodal AI for Early Detection and Risk Prediction of Alzheimer’s Disease

This fully funded 4-year PhD studentship at the University of Bristol focuses on developing interpretable artificial intelligence (AI) models for early detection and risk prediction of Alzheimer’s disease (AD). AD is the leading cause of dementia and a major public health challenge, and reliable early prediction before irreversible neurodegeneration occurs could transform prevention and intervention strategies. The project aims to build predictive models using multimodal data, including wearable sleep time-series, polygenic risk scores (PRS), APOE ε4 genotype, and clinical risk factors. Genetic inputs will emphasize PRS and established AD risk markers, ensuring feasibility and biological relevance within the PhD timeframe. Whole genome sequencing (WGS) will be considered only as an exploratory option, contingent on time and data readiness. Students will integrate sleep profiles, genetic risk, and clinical variables using advanced approaches such as time-to-event modelling and deep learning architectures. Explainable AI methods will be applied to identify interpretable sleep–genetic–risk interactions, ensuring clinical usability and relevance. The project includes clinical validation within the University of Bristol Brain Health Clinics, working closely with clinicians to evaluate model interpretability and potential integration into real-world decision-making pathways. The research environment is highly interdisciplinary, linking engineering, neuroscience, psychiatry, and NHS dementia services, with access to world-leading datasets and strong clinical translation pathways. The supervisory team includes experts in AI & Digital Health, Cognitive Neurology, Psychiatry & Sleep, Digital Health & Sleep Neuroscience, and Neuropsychiatry. Applicants should have a strong quantitative, computational, biomedical, or clinical background, with experience in AI, machine learning, statistics, mathematics, computer science, engineering, genetics, neuroscience, psychology, psychiatry, medicine, or related disciplines. Programming experience (Python or R) and strong analytical skills are essential. A first-class or strong upper second-class degree and ideally a Master’s degree (or equivalent experience) are required. International applicants are welcome but must self-fund the difference between Home and Overseas tuition fees, with documented evidence. The studentship is jointly funded by BRACE Dementia Research and the University of Bristol, covering UK Home tuition fees, a tax-free stipend at UKRI rates, and research/training costs. The application deadline is March 31, 2026, with shortlisted candidates invited to discussions in mid- to late March and a planned start date in September 2026. For further information or enquiries, contact Dr Qiang Liu at [email protected]. Apply online via the University of Bristol portal and ensure all required documentation is provided.