103 parallel-computing-numerical-methods Postdoctoral research jobs at University of Oxford
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on understanding the spread and control of human infectious diseases using modelling and pathogen genomics. This is a short-term opportunity to apply machine learning methods to two key projects. First, you will
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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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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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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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lab has developed the OrthoFinder comparative genomic methods. OrthoFinder has become widely-used in comparative genomics research, it powers many popular databases of online genomic information, and
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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
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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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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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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