183 parallel-computing-numerical-methods research jobs at University of Oxford in United Kingdom
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The Oxford Internet Institute has an exciting opportunity to join the Governance of Emerging Technologies research programme, working under the supervision of Professor Brent Mittelstadt and
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/workforce-and-learning-research-group ). The Compound Pressures project is a realist review funded by the NIHR HSDR programme. The project aims to understand how multiple and intersecting pressures, such as
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, Physics, Engineering or a relevant subject area, (or be close to completion) prior to taking up the appointment. The research requires experience in statistical mechanics method development, with
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. The group is working to uncover how peptides presented by MHC-I regulate KIR recognition and NK cell effector function, using novel methods to define KIR peptide-specificity and generate tools for further
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and manipulation and a knowledge of relevant statistical methods. You will possess exceptional organisational skills, an ability to work efficiently with collaborators and to supervise and educate
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We are inviting applications for an exciting new post for a Research Assistant to work with Dr Megan Kirk Chang on an interdisciplinary research program on the Oxford Health BRC Preventing Multiple
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hepatitis and liver disease. This post is funded by the National Institute for Health and Care Research (NIHR) as part of a significant research programme that leverages large-scale healthcare datasets
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the performance of lithium ion technologies. To support the programme, the post holder will be required to carry out research on characterisation of battery degradation, with a particular focus on the application
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We are seeking five full-time Postdoctoral Research Assistants to join the Computational Health Informatics Lab at the Department of Engineering Science, based at the Institute of Biomedical
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with the possibility of renewal. This project addresses the high computational and energy costs of Large Language Models (LLMs) by developing more efficient training and inference methods, particularly