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Position Summary Working on research program centered on unraveling the intricate molecular mechanisms that govern DNA repair and replication, with a particular focus on nick sealing processes by human DNA
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and great opportunity of interdisciplinary training in machine learning and functional genomics. The project combines cutting-edge computational approaches, especially state-of-the-art machine learning
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research. The ideal fellow will be interested in developing and applying novel computational algorithms to novel datasets generated in the setting of non-neoplastic and neoplastic disease. Key
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to 8 hours/day, lifting <30 lbs, may view computer up to 8 hours/day. Shift Generally Monday – Friday, 8a-5p with some flexibility Job Summary This position is designed to have 70% clinical time, 15
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Participate in teaching and supervision activities, in line with the candidate’s profile and interests The research activities will be hosted by the Parallel Computing and Optimisation Group (PCOG) at SnT
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and impactful research into intrinsic motivation, with a particular focus on building computational theories that predict human behaviour in the absence of extrinsic rewards, and testing them using
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faculty working on questions related to the ecology, evolution and conservation of biodiversity throughout the world, while the associated Interdisciplinary Program in Ecology and Evolutionary Biology links
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platform for launching an independent academic career focused on AI and the future of scientific practice. Responsibilities Build and maintain computational data pipelines to collect and structure evidence
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to treatment. We are seeking highly motivated individuals to develop and implement innovative computational approaches for analyzing high throughput genomic and epigenomic data, including but not
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collaboration. Department/Program & College Description: At VDPAM, we lead the future of food animal and population medicine. As a global center of excellence, we are recognized for our expertise, valued for our