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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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Old Road Campus, Headington, Oxford, OX3 7LF 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...
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from backgrounds, including computational chemistry, bioinformatics, systems biology, physics and machine learning. The project offers a unique opportunity to collaborate closely with experimental
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, systems biology, physics and machine learning. The project offers a unique opportunity to collaborate closely with experimental scientists and contribute to translational advances in synthetic biology and
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from backgrounds, including computational chemistry, bioinformatics, systems biology, physics and machine learning. The project offers a unique opportunity to collaborate closely with experimental
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machine learning. The position will involve working with different research groups in the Department of Computer Science at the University of Cambridge, UK. In this collaborative project, we will apply
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will involve the development of advanced data analytic and machine learning techniques applied to the processing of sensing signals obtained from advanced fibre-optic communication systems. You will be
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in machine learning and/or computer security and Experience working with LLMs or agent-based systems. Informal enquiries may be addressed to adel.bibi@eng.ox.ac.uk For more information about working at
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and Telecommunications Architectures for Tectonic and Infrastructure Characterisation - https://ecstatic-project.eu/ ) The role will involve the development of advanced data analytic and machine
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A position exists for a part-time Research Assistant in the Department of Applied Mathematics and Theoretical Physics to work on the development of novel machine learning methods with applications