University of Exeter
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Fully Funded PhD Studentship in Computer Vision, AI, and Biomechanics at University of Exeter University of Exeter in United Kingdom
Degree Level
PhD
Field of study
Computer Science
Funding
Fully funded PhD studentship. The project is ERC-funded through Professor Sarah (Sallie) Lamb's STEPPING OUT project. Funding details beyond full support are not specified.
Deadline
Dec 8, 2026
Country
United Kingdom
University
University of Exeter

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About this position
Opportunity for a fully funded PhD studentship at the University of Exeter in a project combining computer vision, deep learning, artificial intelligence, and biomechanics.
The research sits within Professor Sarah (Sallie) Lamb's ERC-funded STEPPING OUT project and focuses on analysing video of older adults moving in a simulated home scene to predict instability and falls before they happen. This is a strong fit for applicants interested in movement analysis, human behaviour, health technology, and AI for real-world impact.
Backgrounds welcomed include computer science, data science, AI, engineering, applied mathematics, biomechanics, or related fields. The post does not mention a specific scholarship programme name, but it clearly states the studentship is fully funded.
The application deadline is midday on Tuesday 8 December 2026, and the project is scheduled to start in September 2027. Interested candidates should read the project description and apply via the University of Exeter application link.
Funding details
Fully funded PhD studentship. The project is ERC-funded through Professor Sarah (Sallie) Lamb's STEPPING OUT project. Funding details beyond full support are not specified.
What's required
Applicants with backgrounds in computer science, data science, AI, engineering, applied mathematics, biomechanics, or related fields are welcome. The post does not specify GPA, language test, or other formal entry requirements.
How to apply
Review the project description and submit an application through the University of Exeter PhD application link. Applications close at midday on Tuesday 8 December 2026.
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