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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

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Country

United Kingdom

University

The University of Manchester

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Keywords

Computer Science
Environmental Science
Psychology
Information Technology
Deep Learning
Artificial Intelligence
Urban Planning
Computer Vision
Salud Pública
Statistics
Video Analytics
ML

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About this position

[4-year studentship with an annual stipend at the UKRI minimum rate of £21,805 per year plus £1,000 per year enhancement, and a research training support grant of up to £20,000 for the full programme. Open to Home (UK) and international applicants; project is in competition for funding.]

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

University Name
Country flag

United Kingdom

Research Interests

Epidemiology

Project Management

Academic Collaboration

Pandemic Preparedness

Sars-cov-2