54 machine-learning-"https:"-"https:"-"https:" Postdoctoral positions at University of Oxford in United Kingdom
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Applications are invited for a Postdoctoral Research Associate in Machine Learning for Chemistry to work in the research group of Professor Volker Deringer at the Department of Chemistry. About the
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Oxford Population Health (the Nuffield Department of Population Health) provides an excellent environment for multi-disciplinary research and teaching and for professional and support staff. We work together to answer some of the most important questions about the causes, prevention and...
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We are seeking two full-time Postdoctoral Research Assistants in Machine Learning to join the Foerster Lab for AI Research group at the Department of Engineering Science (central Oxford). The post
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Reporting to the PI, Prof Erin Saupe, the post holder will be a member of a research group with responsibility for carrying out research for ERC grant ‘Determining the drivers of extinction across space and time’. The post holder will provide guidance to less experienced members of the research...
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Engineering, Mathematics, Statistics, Computer Science or conjugate subject and have a strong record of publication in the relevant literature. Good knowledge of machine learning algorithms is essential, as
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of machine learning-based automated ultrasound video analysis models that incorporate temporal reasoning. The research will also include work that aims to understand how human behaviour may change with
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near completion) and have publications in rejection learning or learning-to-defer techniques. You should also have experience of original machine learning architecture design and ideally have prior
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of probability of statistical machine learning. They will possess sufficient specialist knowledge in network analysis and uncertainty quantification in machine learning and have the ability to manage
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responsible for the design and testing of original machine-learning based methods for fetal heart biomarker discovery from the CAIFE image and video dataset. The full-time post is funded by InnoHK and is fixed
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predictive control of carbon mineralisation through high-throughput mineralogy and machine learning.” This is an exciting opportunity to contribute to innovative research at the interface of mineralogy