102 parallel-and-distributed-computing Postdoctoral positions at University of Oxford in United Kingdom
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We are seeking a talented and motivated researcher to join the Mead Group to contribute to a major research programme, focused on understanding and preventing disease progression in
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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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experiments on fish in the field or the lab, coupled with strong computational skills in R and/or Python relating to data management and analysis. An essential requirement for this role is that the post holder
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assessing sustainable routes for large-scale removal of greenhouse gases from the atmosphere. As well as interact with others in this programme within the duration of the post, and the results of the PDRA
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posters locally and at national and international conferences, as well as participate in MRC grant’s research programme led by Prof Marco Fritzsche. You must hold a relevant PhD/DPhil (or be near completion
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computational sciences, decision-maker education campaigns, and training the next generations of technology governance leaders. It is one of the few organisations in the world to focus on the governance of AI
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collaboration with the Translational Gastroenterology Unit (TGU) and the Ludwig Institute of Cancer Research (LICR) we aim to develop a computer guided endoscopy image recognition system that will support
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engineering, computer science or other field relevant to the proposed area of research. You should have a good track record of robotic publications/presentations in the field of healthcare, possess sufficient
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. Keith Channon – a 5 year renewable award that underpins the work of the group. You will lead a programme of research in the molecular mechanisms of cardiovascular disease, that may include a range of
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associated computing code for modelling avian influenza outbreaks in Great Britain (GB). One position will focus on modelling the risk of virus invasions into GB in different locations and at different times