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out rigorous and impactful research into the computational mechanisms of human learning using deep neural network models, and disseminating the findings within the research group, across the wider
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work packages, you will quantify how resistance spreads in time and space, trace the origins of human infections, and model source transitions to identify key points for intervention. The project will
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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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’ (PHOENIX), led by Associate Professor Thomas Aubry (University of Oxford). Using a combination of laboratory experiments, field work and numerical modelling, PHOENIX aims to improve our understanding
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structural properties of nanostructures and nanoparticles. We combine expertise in nanofabrication, laser science, nonlinear optics, sensing, advanced imaging techniques and numerical modelling. About the role
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researchers will extend and apply the ideas of active matter physics in biological contexts, developing theories and cell-scale and continuum computational models. The work will focus on identifying physical
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models of mechanotransduction. Research projects are highly interdisciplinary, aiming to integrate in vitro biochemical and cell biological techniques with in vivo models and clinical samples. Recent
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, economics, environmental science). You will bring expertise in food systems modelling, supported by a strong technical background that may span areas such as data science, input–output analysis, applied
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for carrying out research to develop iPSC-derived lung cell models. Working within a team of biochemists, cell and structural biologists, you will perform experimental work to apply omics technologies, advanced
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navigation algorithms and machine learning models on physical robot platforms. We are particularly interested in candidates with expertise in generative AI and curriculum learning applied to robotics, as