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Field
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studentship in Synthetic andPhysical Organic Chemistry available from October 2026, to work under the supervision of Prof. Paul McGonigal and Dr Alyssa-Jennifer Avestro in the Department of Chemistry at
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Advances in computing, experiments, and information will continue to reshape engineering in the next decade. This PhD position will nurture a multidisciplinary innovator with the tools to unravel
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-on experience in both laboratory and computational approaches, equipping you with a strong skill set for a career in evolutionary genetics, genomics, or bioinformatics. Person Specification This project is ideal
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degree or a Master’s programme and/or have worked for some years; or are currently enrolled in a PhD programme overseas Upon successful completion of the PhD programme, the scholar will be considered
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supervision across the Schools of Chemistry, Pharmacy & Pharmacology and of Environmental Sciences, gaining experience in both laboratory and computational approaches. You will benefit from two 3-months
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expected to receive a first or upper-second class honours degree in anEngineering, Computer Science, Design, Mathematics, Physics or a similar discipline. A Postgraduate Masters degree is not required but
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. Communication of scientific findings through publications and conferences. Person Specification A highly motivated candidate with: A degree or equivalent in numerate, computational, or environmental subject areas
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at the UKRI rate (£20,780 from 1/10/25). There is an enhanced budget for project costs (including travel) of £20,000. Applications are made to the Metamaterials programme for a PhD in Physics/Engineering. We
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of Edinburgh and will be jointly supervised by: Dr Dominik Leichtle, School of Informatics, University of Edinburgh Dr Elham Kashefi, School of Informatics, University of Edinburgh Dr Ivan Rungger, National
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ecosystem modelling using both field-based and modelled physical and biological data. Collaboration with Centre for the Environment, Fisheries and Aquaculture Science will provide exposure to how science