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local contexts. The successful candidate will be encouraged to contribute to all components of the group's programme but will be expected to i) map the range of primary and community health services
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modelling to study the causes and consequences of extreme chromosomal instability in these cancers. The role will involve: - Learning and applying cytogenetic methods for generation and analysis of chromosome
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RNA or ribosome-associated structures. Computational and Bioinformatic Analysis Handling and interpreting large datasets, sequence conservation, RNA structure modelling, and more. You will be supported
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computational scientists to develop advanced algorithms and models. Research and validate potential biomarkers associated with breast cancer progression, treatment response, or patient outcomes, using
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but not limited to biology, computer science, engineering, population health, modelling) and an interest in policy A demonstrable ability to critically engage with technical policy documents related
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, computational modelling, and image analysis would also be valuable to the role. The successful applicant will be an excellent team player, highly solution-orientated and self-motivated. Excellent interpersonal
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oversight, accountability and leadership of the Estates Management functions to drive quality, efficiency and compliance. They will also act as a key interface with the Estates Development, Programme
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The University of Cambridge is seeking a highly motivated, organised and initiative-focused computational biologist to join a team of clinical, immunological and computational researchers within CG
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Applications are invited for a University Assistant Professorship in the broad area of Machine Learning. The successful candidate will join the Computational and Biological Learning Lab (CBL