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Caroline Jay
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PhD Studentship: Automating Behavioural Observation to Understand the Effects of the Environment on Health The University of Manchester in United Kingdom
Degree Level
PhD
Field of study
Computer Science
Funding
Available
Deadline
Dec 18, 2026
Country
United Kingdom
University
The University of Manchester
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About this position
This PhD studentship at The University of Manchester focuses on building an AI-enabled system to automate the behavioural observation method MOHAWk (Method for Observing pHysical Activity and Wellbeing). The project sits at the intersection of computer vision, machine learning, and health research, with the goal of turning a manual, labour-intensive coding process into a scalable automated workflow for analysing video footage from public spaces.
The successful student will work on developing and validating models that can identify MOHAWk behaviours in video, compare automated outputs with expert manual coding, and test how well the system performs across different urban and observational contexts. A further emphasis is on understanding robustness, generalisability, and potential bias, making this a strong interdisciplinary project that combines technical AI development with real-world evaluation.
The project also aims to demonstrate the value of the tool through the assessment of a real-world environmental intervention. Expected outcomes include an open-source framework and software for scalable behavioural observation, plus evidence on the strengths and limitations of foundation-model approaches for analysing behaviour in public spaces. The work has potential applications across public health, urban planning, transport, and environmental research.
The main project supervisor is Prof Caroline Jay.
Funding details
Available
What's required
Applicants should hold, or expect to obtain, at least a minimum Upper Second-Class Honours degree (or international equivalent) in a relevant discipline. A background in Computer Science, Artificial Intelligence, Data Science, Software Engineering, Mathematics, Statistics, Physics, Engineering or another related quantitative subject is desirable. Applicants should have an interest in machine learning and data analysis, plus some experience of programming and computational methods. Experience in computer vision, deep learning or video analysis would be advantageous but is not essential.
How to apply
Contact the main project supervisor, Prof Caroline Jay, to discuss the project if desired. Submit a formal application through the online portal and select programme FSE PhD President’s Doctoral Scholarship. Upload the supporting statement, CV, transcripts, and details of two referees; late or incomplete applications will not be considered.
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Professors
Prof at The University of Manchester
United Kingdom
Research Interests
Epidemiology
Project Management
Academic Collaboration
Pandemic Preparedness
Sars-cov-2
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