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the Electrochemical Engineering Science Group and work within Dr Daniel Niblett's team on the five-year UKRI EPSRC ION-H2 Fellowship. The programme combines computational modelling, machine learning
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an ambitious researcher with expertise in artificial intelligence, machine learning, or computational statistics, and a demonstrated interest in applications to human genetics and/or population health. We
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fluid mechanics, computational geometry, meshing, computational graphics, computational vision, or scientific machine learning in general. Successful candidates will join a community of researchers in
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mathematical structures and computational algorithms underlying modern machine learning and artificial intelligence. Relevant themes include geometric and algebraic methods for learning, structure-preserving
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September and December 2026. We seek an ambitious researcher with expertise in artificial intelligence, machine learning, or computational statistics, and a demonstrated interest in applications to human
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The Josef Korbel School of Global & Public Affairs is seeking qualified candidates for a postdoctoral fellowship. This scholar will reside at the University of Denver for one full academic year. This post-doc
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an ambitious researcher with expertise in artificial intelligence, machine learning, or computational statistics, and a demonstrated interest in applications to human genetics and/or population health. We
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by applying existing and novel computational biology, bioinformatic, and machine learning algorithms to sequencing datasets and correlating them with multi-dimensional clinical datasets that contain
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the following will be a plus: • Optical instrumentation, single-molecule/ super-resolution microscopy, magnetic/optical tweezers, ultrafast spectroscopy, or other in-situ operando imaging tools • Machine
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Oden Institute for Computational Engineering and Sciences | Austin, Texas | United States | 2 months ago
genetic data Multimodal machine learning for biological discovery Translational genomics and risk modeling The fellow will work in an environment that emphasizes methodological innovation, statistical rigor