Grainne McGill
2 months ago
PhD in Integrating Housing and Health Data for Early Intervention (Architecture, Computer Science, Public Health) University of Strathclyde in United Kingdom
Degree Level
PhD
Field of study
Computer Science
Funding
Funding covers tuition fees for Home UK applicants for 3 years and provides a stipend at the Research Council rate (estimated £20,780 for Session 2025/26). International applicants must cover the difference between home and international tuition fees (estimated at £86,838). The stipend cannot be used for this difference. Additional self-funded or externally funded students may be considered.
Deadline
Expired
Country
United Kingdom
University
University Of Strathclyde

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Where to contact
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About this position
The University of Strathclyde is offering a funded PhD studentship titled “Integrating Housing and Health Data for Early Intervention” as part of the Strathclyde Centre for Doctoral Training (SCDT) in Energy-Efficient Indoor Climate Control for Optimised Health. This interdisciplinary opportunity is co-supervised by Professor Marc Roper (Computer & Information Sciences) and Dr Grainne McGill (Architecture), and aims to develop innovative approaches for linking housing, health, and environmental data to inform prevention-focused decision-making and improve public health outcomes.
The research will focus on integrating datasets from housing and healthcare systems to enable early identification of indoor environmental risks such as pollutant exposure and poor ventilation, which are key factors in respiratory illnesses, especially among children. The project will explore data integration methods, governance models, and referral mechanisms to support early intervention for high-risk households, while aligning with current policy developments like Awaab’s Law and the Healthy Homes Standard.
Students will benefit from a vibrant research environment, interdisciplinary training in indoor air quality, human behaviour, data analytics, and machine learning, and opportunities to engage with clinicians, industry specialists, and the public. The programme includes professional development, scientific writing training, and support for external funding applications. Successful candidates will join a collaborative cohort and receive a stipend and tuition coverage for UK home applicants. International students may apply but must secure funding for the tuition fee difference.
Eligibility requires an upper-second or first class BSc Honours degree or a Masters in relevant fields such as Data Science, Computer Science, Health Informatics, AI, Statistics, Architecture, Building Science, Public Health, Environmental Health, Social Policy, or Digital Health. Applicants should demonstrate strong data analysis skills, experience with Python or R, understanding of data integration and governance, knowledge of housing and health systems, and excellent communication and stakeholder engagement abilities. English language proficiency is required for non-native speakers.
To apply, candidates should submit a CV, cover letter, two academic references or contact details, degree transcripts, a substantial writing sample, and English language test results (if applicable) to [email protected]. Early applications are encouraged, and shortlisted candidates will be invited for an online interview. The application deadline is 5 January 2026.
This PhD offers a unique opportunity to work at the intersection of architecture, computer science, and public health, contributing to evidence-based solutions for healthy buildings and prevention-focused public services.
Funding details
Funding covers tuition fees for Home UK applicants for 3 years and provides a stipend at the Research Council rate (estimated £20,780 for Session 2025/26). International applicants must cover the difference between home and international tuition fees (estimated at £86,838). The stipend cannot be used for this difference. Additional self-funded or externally funded students may be considered.
What's required
Applicants must hold an upper-second or first class BSc Honours degree or a Masters degree in a relevant area such as Data Science, Computer Science, Health Informatics, Artificial Intelligence, Statistics, Architecture, Building Science, Public Health, Environmental Health, Social Policy, or Digital Health. Strong interest and prior experience in healthcare data analytics, preventative health, environmental data, digital health systems, building performance, AI, or machine learning is required. Candidates should have strong data analysis skills, experience with Python, R, or similar platforms, understanding of data integration and governance, knowledge of housing and health systems, excellent communication and stakeholder engagement skills, and experience in research. English language test results are required for non-native speakers. International applicants must provide proof of funding for the tuition fee difference.
How to apply
Send your CV, cover letter (max 3 pages), two academic references or contact details, degree transcripts, a substantial writing sample, and English language test results (if applicable) to [email protected]. Confirm your ability to start in your cover letter or email. Early applications are encouraged. Shortlisted candidates will be contacted for an online interview.
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