33 genetic-algorithm-computer Postdoctoral positions at University of Oxford; in United Kingdom
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About the role We have an exciting opportunity for a highly motivated Postdoctoral Research Scientist in Computational Biology to join the Oxford Vaccine Group (OVG) as part of the Correlates
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Location: South Parks Road, Oxford OX1 3QU About the role We are looking for a Postdoctoral Research Associate in Computational Biology to join the group of Dr Rebecca Berrens. This primarily dry
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learning models to accelerate mixed-integer solvers Implementing and analysing online optimisation algorithms for real-time grid balancing Liaising with project partners (NESO and University of Strathclyde
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. statistics, mathematics, computer science, statistical or population genetics, or a related discipline), and a strong motivation to work on problems in genetics and you will also have relevant coding
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for Human Genetics, Oxford Global Health, and the NIHR Oxford Biomedical Research Centre. To be considered, you will hold a PhD/DPhil in bioethics, medical ethics, or other subject relevant to infectious
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with an international reputation for excellence. The Department has a substantial research programme, with major funding from Medical Research Council (MRC), Wellcome Trust and National Institute
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molecular biology and genetics, and experience with DNA-binding proteins are beneficial. They will use structural and biochemical approaches to determine how Exo7 recognises and processes DNA-protein
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initiatives. To be considered, you must hold, or be close to completion of, a relevant PhD/DPhil in one of the following subjects: quantitative, genetic or molecular epidemiology, medical statistics
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of mechanotransduction and protein synthesis machinery to join the Tzima/Reader research group at the Centre of Human Genetics, within the University of Oxford. The Tzima/Reader research group is at the cutting edge
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) and therapeutically tractable tumour-microenvironment interactions (Andrade et al., Nature Communications 2024), and are now expanding into using spatial biology, in vivo CRISPR screening and genetic