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Jack Stone

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Fully Funded PhD in Modelling the Impact of Homelessness and Social Exclusion on Health University of Bristol in United Kingdom

Degree Level

PhD

Field of study

Data Science

Funding

Fully funded PhD with home/UK student fees covered plus a stipend.

Country flag

Country

United Kingdom

University

University of Bristol

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Keywords

Data Science
Epidemiology
Biology
Mathematics
Mathematical Modeling
Health Disparities
Medical Science
Salud Pública
Economics
Social Exclusion
Statistics

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About this position

Funded PhD opportunity at the University of Bristol in the GEM-B Modelling Group and the NIHR Health Protection Research Unit in Behavioural and Social Sciences Evaluation (HPRU BSE).

The project is titled Modelling the impact of homelessness and related social exclusion on health in the UK. It is an interdisciplinary PhD combining mathematical modelling and epidemiological modelling to study how homelessness and related forms of social exclusion affect health outcomes, and how interventions and policies may reduce health inequalities.

This opportunity is especially relevant for candidates interested in Public Health, Mathematics, Statistics, Medical Science, Biology, and related quantitative fields such as data science and economics. Strong quantitative skills are required, and prior modelling experience is desirable but not essential.

The project will be undertaken in close collaboration with the UK Health Security Agency (UKHSA), offering an applied research environment connected to public health policy and health protection. Funding includes home/UK PhD fees plus a stipend, making this a fully funded doctoral position for eligible applicants.

Applications are being considered on a rolling basis, so interested candidates should apply early. To express interest, send a CV and a short cover email describing your background, research interests, and relevant experience to Peter Vickerman and Jack Stone at the email addresses listed in the post.

Funding details

Fully funded PhD with home/UK student fees covered plus a stipend.

What's required

Applicants should have strong quantitative skills and backgrounds such as epidemiology, mathematics, statistics, data science, public health, economics, or related disciplines. Previous modelling experience is desirable but not essential.

How to apply

Send a CV and a brief cover email outlining your interests and relevant experience to [email protected] and [email protected]. Applications are considered on a rolling basis, so early contact is encouraged.

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Professors

Associate Professor in Infectious Disease Mathematical Modelling

University Name
Country flag

United Kingdom

Research Interests

Epidemiology

Statistics

Medical Science

Health Disparities

Social Exclusion