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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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About the Role We have an opportunity for a Postdoctoral Research Associate in Machine Learning to join PHURI, within the research team of Dr Joseph Taylor working on improving our understanding and
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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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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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) in machine learning or a closely related field you should possess sufficient specialist knowledge in the discipline to work within established research programmes and have an ability to manage own
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on and defensive mechanisms for safe multi-agent systems, powered by LLM and VLM models. Candidates should possess a PhD (or be near completion) in Machine Learning or a highly related discispline. You
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Machine Learning, Statistics, Computer Science or closely related discipline. They will demonstrate an ability to publish, including the ability to produce high-quality academic writing. They will have the
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About the Role We are seeking an enthusiastic and motivated postdoctoral researcher to apply advanced data analytics and machine learning techniques to real-world clinical data in the field of viral
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Postdoctoral Researcher in Machine Learning of Isomerization in Porous Molecular Framework Materials
broad range of applications. Computational chemistry and Machine Learning increasingly underlies MFM research to search or screen candidate MFMs prior to synthesis. A major drawback when applying