67 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Mines Paris PSL" Postdoctoral research jobs at University of Oxford in United Kingdom
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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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to the 30th September 2026. We are looking for outstanding machine learning researcher to join the Torr Vision Group and work on AI Scientists: systems that use foundation models, AI agents, and robotics
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* together with relevant experience. You will have a strong technical background in machine learning, especially RL and LLMs. An ability to work independently and as part of a collaborative research team is
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the leadership of Principal Investigator Dr Andrew Siemion. Listen's interdisciplinary research has synergies with many of the department's research priorities, including exoplanet studies, machine learning
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machine learning methods to model changes in the brain over the lifespan, including brain structure and function, and how those changes relate to environment and genomics. What We Offer As an employer, we
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the sequence of the human genome and the development of common diseases. You will work on a collaborative project that aims to develop Machine Learning and laboratory-based approaches, for decoding how the human
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of Oxford offers an attractive range of competitive benefits available to all staff for both work and personal life - https://hr.admin.ox.ac.uk/staff-benefits Committed to equality and valuing diversity We
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@cardiov.ox.ac.uk Georgia Broom – cvm_personnel@cardiov.ox.ac.uk The University of Oxford offers an attractive range of competitive benefits available to all staff for both work and personal life - https
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, socially grounded approaches to disease threats affecting animal and human health — learning from those who manage biological risks in everyday settings rather than relying solely on top-down models. Working