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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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, Oxford, Leeds, Reading, and Birmingham) and international (Utrecht University, ETH Zurich, Université Catholique de Louvain, etc.) scientists to use new modelling resources and methods to elucidate drivers
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dendrite patterning, axonal guidance and synaptogenesis, and neuronal regeneration (Cheerambathur et al. , Ouzounidis et al. , Domingos et al. ). By leveraging the well-established neuronal model, C. elegans
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, and enabling data-driven improvements in patient care. You will have opportunities to apply foundation models—including large language models (LLMs) to real-world clinical data. You will work with well
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, defensive mechanisms and related topics to the safe deployment of systems contain multiple LLM and VLM powered models. You will be responsible for Developing and implementing; capability evaluations, attacks
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the cellular and molecular mechanisms driving tumour development. In this role, you will support a team of scientists using genetically engineered mouse models (GEMMs) and transplantable tumour models (e.g
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Professor Chris Russell. This is an exciting opportunity for you to work at the cutting edge of AI, contributing to a major shift in how we understand and apply foundation models. The position is full-time
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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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postdoc to work on a project funded by the Biotechnology and Biological Sciences Research Council (BBSRC). The post is for two years to study the role of the microbiome in olfaction using mouse models
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also highly valuable. The successful candidate will be expected to work on estimating dynamic models of medical spending and savings and is expected to publish in high-impact academic journals, and to