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of equilibrium dynamics using tensor networks to solve partial differential equations, with applications to many-body quantum systems, as well as computational fluid dynamics and plasma dynamics. The successful
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collaborative links thorough our collaborative network. The researcher should have a PhD/DPhil (or be near completion) in robotics, computer vision, machine learning or a closely related field. You have an
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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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hold a relevant PhD/DPhil (or be near completion) with experience in high-speed/high-enthalpy wind tunnels. You should have a strong publication record and familiarity with existing literature in
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Computational Neuroscience and related fields as part of the Medical Research Council, UKRI grant “Algebraic topology bridging the gap between single neurons and networks”. They will be expected to conduct
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research programme at Oxford. Candidates should hold a PhD in biomedical engineering, computer science, medical physics, statistics, or a related field. A strong track record of first-/senior or co-author
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Modernising Medical Microbiology (MMM) unit at the University of Oxford (https://www.expmedndm.ox.ac.uk/mmm). You will be joining a highly interdisciplinary team of approximately 40 clinicians, computational
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hepatitis and liver disease. This post is funded by the National Institute for Health and Care Research (NIHR) as part of a significant research programme that leverages large-scale healthcare datasets