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of climate science, statistical methodology, and computational modelling. The PROTECT project is part of the ARIA-funded programme on climate tipping points and aims to improve the scientific and statistical
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Research Hub. Funded by the Higher Education Authority of Ireland, SLSS is an ambitious programme of activity. It brings together two academic institutions (University of Limerick and Queen’s University
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their relationship with treatment responses and disease activity. This is an excellent opportunity to contribute to a collaborative research program dedicated to improving our understanding of ALS and informing future
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Medicine, Statistical Genetics, Bioinformatics, Computational Biology, or a related quantitative discipline. You will also demonstrate a proficiency in statistical programming using R and/or Python, with
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have completed, or be close to completing, a PhD/DPhil in a relevant quantitative field such as computational social science, computer science, or cognitive science. They will have a demonstrable track
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slavery and war. Structured around four interconnected research strands—(Re)conceptualising, Understanding, Forecasting and Tackling—the Centre’s programme aims for far-reaching insights that transform
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for teaching and research at the Guy’s and Waterloo Campuses have been greatly enhanced since 1998 through a capital investment programme of approximately £200 million, which has provided state-of-the-art
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We are seeking a Post-doctoral research associate to investigate the mechanisms of mutagenesis in the human genome. The Opportunity: To lead a programme of original, high-quality research focusing
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computational pipelines for the analysis of single-molecule microscopy data. Research in the Gruszka Lab centres on physical and molecular mechanisms of biological processes using interdisciplinary strategies
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are seeking to appoint a postdoctoral research associate as part of a UKRI Future Leader Fellowship funded research programme. The successful candidate will work as part of a team to develop and apply deep