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) information-theoretic active learning, and c) capturing uncertainty in deep learning models (including large language models). The successful postholder will hold or be close to the completion of a PhD/DPhil in
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an industry partnered project for translational drug discovery. The role will involve analysing large scale omics and spatial datasets from both primary patient samples and advanced in vitro model systems
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Claudia Monaco’s research group at the Kennedy Institute of Rheumatology. In this role, you will apply single cell biology and cell signalling techniques combined with in vivo and in vitro models
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with the possibility of renewal. This project addresses the high computational and energy costs of Large Language Models (LLMs) by developing more efficient training and inference methods, particularly
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/weather observational and modelling products would be of a substantial value. Furthermore, experience with epidemiological modelling and/or attribution of extreme events and their impacts in a changing
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generate key structural and biophysical data to support the design of small molecule inhibitors with particular focus on protein production and crystallisation, solving protein-ligand structures, fragment
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this hydrogen generation model with the ammonia synthesis module. Find out more about the Hayward research and group at: https://www.chem.ox.ac.uk/people/mike-hayward. About you Applicants must hold a
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, activation, and effector functions in preclinical models of autoimmunity. This research is part of a broader effort to define how inhibitory receptors tune T-cell responses in health and disease, ultimately
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project to develop a systematic framework for reconstructing the evolutionary histories of pathogens. The role involves using viral sequence data and models of sequence evolution to investigate both
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We are seeking to appoint a highly motivated Postdoctoral Researcher with expertise in innate immune responses to cancer, in vivo/in vitro experimental models, and advanced molecular techniques