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How to apply: uom.link/pgr-apply-2425 This 3.5-year PhD studentship is open to Home (UK) applicants and EU students with settled status. The successful candidate will receive an annual tax-free
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(PhD) training and mentorship. Vacancies are open to medically qualified trainees in any clinical discipline with an academic interest in cancer and who are based anywhere in the UK. All candidates
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machine learning. The position will involve working with different research groups in the Department of Computer Science at the University of Cambridge, UK. In this collaborative project, we will apply
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, alongside other major global pathogens including hepatitis B and C viruses, HIV, SARS-CoV-2 and Dengue. The postholder will be responsible for designing and optimising sequencing approaches, leading data
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on Africa, including Zimbabwe where we have previously collected pilot data with collaborator Dr McDonald Matika. Although potential second countries in each continent have already been identified, the PhD
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. You will also help evaluate AI tools in real-world healthcare settings, supervise PhD students, and contribute to shaping the future direction of AI in the Unit. This post is full time and fixed term
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start dates also possible) Email: david.duncan@nottingham.ac.uk About the project We are recruiting applicants for a fully funded PhD studentship in the School of Chemistry at the University of Nottingham
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Funding amount Minimum tax-free stipend at the current UKRI rate is £20,780 for 2025/26, and RTSG £7000 Hours: Full-time Closing date: 30 October 2025 The project: This PhD studentship is an
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One fully funded, full-time PhD position to work with Prof. Mahesh Marina in the Networked Systems Research Group at the School of Informatics, University of Edinburgh. The broad aim
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Boreal forest recovery after clear-cut: We are looking for a highly motivated PhD student to collect data on and model hydro(geo)logy and greenhouse gas exchanges of boreal forests after