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approach including empirical data analysis, experiments, and theoretical modelling to develop science-based management strategies for the restoration of woodland ecosystems. We will collect, and collate from
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/or modelling is essential. Experience in machine learning, computer vision, and computer programming is desirable. In addition, applicants should be highly motivated, able to work independently, as
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start dates: 1 October 2025 (Enrolment open from mid-September) Supervisors: Hari Arora (Biomedical Engineering), Richard Johnston (Materials) and Iain Whitaker (Medicine) Aligned programme of study: PhD
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models to predict defect behavior without the computational cost of DFT. The successful applicant should have or expect to achieve at least a 2.1 honours or equivalent at Bachelors or Masters level in
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-edge biological modelling to understand exactly how IIDs spread in nurseries. The project aims to develop improved intervention guidelines to prevent high mortality IIDs, considering what’s realistic and
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including predictive modelling, computer vision and epidemiology. The student will join an established team of investigators, including statisticians, epidemiologists, image scientists, and clinicians
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enrichment strategies can be tailored for best conservation success. This PhD project will combine empirical fieldwork with cutting-edge spatio-temporal ecological modelling of systems dynamics to investigate
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-modal datasets. It will use advanced analytical models to generate evidence about new and existing inflammatory pathways and how these will impact the progression of dementia. The PhD (DPhil) programme
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for constraining the spin of the compact object being lensed which will involve both theoretical and computational modelling. If you wish to discuss any details of the project informally, please contact: Prof
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diseases, but is frequently misunderstood, forgotten, and missed. As a toxic proteinopathy that leads to progressive fibrosis, it offers a powerful model for studying common pathways in CKD and represents a