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to the project, like biology, physics, applied mathematics previous experience with computational modelling, method development, and numerical analysis applied to biology (or allied fields like neuroscience and
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experience with computational modelling, method development, and numerical analysis applied to biology (or allied fields like neuroscience and medicine) the ability to work effectively in a multi-disciplinary
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group (https://theochem.univie.ac.at/ ) at the Institute of Theoretical Chemistry aims at understanding chemical phenomena using contemporary computational and theoretical methods. We employ and extend ab
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of subsea power cables subjected to combined 3-dimensional waves, currents, and turbulence. This research will be approached by both numerical and physical modelling of power cable's response. The successful
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for carrying out research on numerical engineering of quantum phase transitions. The post holder provides guidance to less experienced members of the research group, including postdocs, research assistants
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Application Deadline 17 Nov 2025 - 00:00 (UTC) Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff
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with these collaborators. The research will involve both analytical work and numerical computations. The balance between analytical and numerical type work is flexible and can depend on the preferences
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frequency domains. The research project aims to exploit these methods to develop an understanding of electron-driven chemistry of water. The successful applicant will work on a specific EPSRC-funded research
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Associate with mathematical modelling and numerical/data analysis background to join our food system resilience project, led by University of Reading, joining a large interdisciplinary team with an excellent
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Research Council (MRC) and the National Institute for Health and Care Research (NIHR), the project aims to advance artificial intelligence (AI) methods that improve the reliability of clinical prediction