This PhD opportunity at the University of Bristol focuses on modelling stroke progression and treatment in the brain, specifically targeting ischaemic stroke—a leading cause of death and disability worldwide. The project aims to advance computational models of stroke development, blood flow, oxygen transport, and fluid dynamics in the human brain. By expanding these models to simulate diverse population groups, the research seeks to help clinicians tailor treatments more effectively and understand the factors influencing patient outcomes.

As part of the EU-wide GEMINI project consortium (https://www.geminiproject.eu), you will collaborate with multidisciplinary teams working to develop and validate advanced models. The PhD will transition existing models from population-averaged to individual behaviour, incorporating parameters such as age, sex, and medical history to enhance predictive accuracy. This approach will support clinicians in making more informed decisions and improve patient care.

There are extensive opportunities for collaboration across the consortium, including involvement in the analysis of large clinical datasets and the construction of statistical models of outcome. The project is based in the School of Engineering Mathematics and Technology, offering access to cutting-edge research facilities and expertise in biomedical engineering, applied mathematics, and engineering mathematics.

Applicants should have a strong quantitative background, ideally in mathematics, engineering, or biomedical engineering, with skills in computational modelling, statistical analysis, or programming. Experience with clinical datasets is advantageous. The University of Bristol requires English language proficiency and a good undergraduate degree (typically a 2:1 or above) in a relevant subject.

Applications are accepted year-round, with no fixed deadline. Funding details are not specified; candidates are encouraged to check the project link for updates. To apply, submit your application via the University of Bristol postgraduate portal, including a CV, academic transcripts, and a personal statement. Informal enquiries to the supervisor are welcome.

For more information and to apply, visit the project page: https://www.findaphd.com/phds/project/modelling-stroke-progression-and-treatment-in-the-brain/?p194886.