539 parallel-computing-numerical-methods-"Simons-Foundation" 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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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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’ (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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instances as required in Commercial Off the Shelf systems – the main system used being REDCap. You will also investigate and implement suitable alternative training delivery methods, at the top level this
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an important role in the Oxford Cancer Clinical Trials Unit providing an effective administrative support service for the team running our clinical cancer research programme. This post is largely office/computer
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and realign how we measure and model populations by infusing new types of data, methods and unconventional approaches to tackle the most challenging demographic problems of our time. We are looking
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social, cultural, and sports clubs. About the Role The Data Quality Team is responsible for monitoring the quality of the student record, programme set-up, system data configuration, and compiling and
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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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continuing tradition of excellence in the subject. The Professor will be expected to provide outstanding research leadership in statistical methods development, bringing with them a vision for the discipline
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University of Oxford’s continuing tradition of excellence in the subject. The Professor will be expected to provide outstanding research leadership in statistical methods development, bringing with them a