111 parallel-computing-numerical-methods-"Simons-Foundation" Postdoctoral positions at University of Oxford in United Kingdom
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settings. We are seeking a highly motivated postdoc to conduct research into this fast-moving area. Directions may include investigating quality evaluation methods for multi-agent systems, attack surfaces
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Engineering, Mathematics, Statistics, Computer Science or conjugate subject; strong record of publication in the relevant literature; good knowledge of machine learning algorithms and/or statistical methods
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focus on ambitious, ‘blue sky’ research for novel methods development relevant for drug discovery analysis pipelines, trial design and operational efficiency. Led by Professor Chris Holmes, and with
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methods suitable for legged systems in physically-realistic simulated environments and on real robots. You should hold or be close to completion of a PhD/DPhil in robotics, computer science, machine
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interdisciplinary research programme involves national and international collaborators. We are a vibrant, enthusiastic, innovative and strategic enterprise with an internationally leading position to make a real
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explores novel aggregation methods at the intersection of AI safety, computational social choice, and judgment aggregation, aiming to formally integrate multi-stakeholder preferences into AI system design
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used in our work centre around optical imaging and spectroscopy and nanofabrication. The work also relies on theory and simulation, specifically focusing on numerical mean-field electrostatics
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project will involve both remote-sensing and field-based observations and data collection. It will provide outputs to the World Bank CAWEP (Central Asia Water Energy Power) programme to aid the design
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Metabolism (OCDEM) on studies related to circadian rhythms in population health. This post is part of a large, interdisciplinary research programme, offering attractive opportunities to work across
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multiple aspects of work to meet deadlines. You will adapt existing and develop new scientific techniques and experimental methods, as well as contribute ideas for new research projects. You will use