PhD Studentship: Multimodal Detection System for Neurodegenerative Decline

Job Description

This PhD aims to develop a low‑cost, multimodal system for early detection of neurodegenerative decline by monitoring everyday behaviours. Subtle changes in attention, visuospatial ability, and motor control can appear years before dementia, but current assessment methods rely on lab-based tasks and specialised equipment, limiting their usefulness for long‑term, at‑home monitoring.

The project will create a smartphone/tablet-based platform that integrates calibration‑free eye tracking, touchscreen interactions, inertial sensing, and simple daily tasks such as reading, tapping games, short walks, and object manipulation. By collecting longitudinal data, the system will learn personalised behavioural profiles and use multimodal deep learning to identify sensitive digital biomarkers that capture cognitive–motor interactions.

Research Goals

• designing ecologically valid tasks
• enabling privacy‑preserving, at‑home data capture with ubiquitous sensors
• developing multimodal machine‑learning models
• refining tasks through Human–AI feedback and patient/public involvement

Funding and How to Apply

The studentship is available from 1 October 2026 for a period of three years, subject to satisfactory progress and includes a tax-exempt stipend, which is currently £20,780 (2025/26) per annum. In addition, full-time tuition fees will be covered for up to three years.

Please submit your application online. When prompted use the reference number 2627-OCT-CATE12. The closing date for applications is 22 May 2026.

For more information contact Professor Lyndon Smith at [Employer hidden — sign up to reveal].