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astrophysics, cosmology, or a related field completed by the start date; strong programming skills; working knowledge of machine learning applied to astrophysics and cosmology, in particular simulation-based
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learning and benthic systems. This position offers an opportunity to contribute to cutting-edge research, particularly advancing the use of remote sensing datasets and machine learning for constructing
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science, energy, national security, and health. Our researchers develop scalable machine-learning models, deep-learning architectures, and data-driven methods for platforms ranging from edge sensors and
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, learning, well-being, social experiences, and decision-making. HARP is developing a longitudinal multimodal research resource to study human-AI interaction and its impacts using student-informed, privacy
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responsibility for carrying out research in rough path theory, machine learning, generative AI and related fields as part of the DataSig II grant “High order mathematical and computational infrastructure
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,(e.g. bioinformatics, computational genomics) and have Machine learning, and bioinformatic genome analysis experience. computer science or bioinformatics, including bacterial population genomics and/or
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proud to be a signatory of the Armed Forces Covenant . an accredited Disability Confident Leader ; autism friendly university , committed to building disability confidence and supporting disabled staff
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shoulders up to 25 pounds. Standing and sitting at computer terminals and laboratory bench completing repetitive tasks for extensive periods of time. Continuous working with materials requiring personal
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pension scheme 38 days annual leave A comprehensive range of childcare services Family leave schemes Cycle and electric car loan schemes Employee Assistance Programme Membership to a variety of social and
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the opportunity for three weeks of training in higher education teaching and learning. The fellow will be expected to lead/contribute to research linking vegetation modelling with the LPJ-GUESS model with tree