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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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of 24 months. The project aim’s to develop new constitutive models to describe the mechanical behaviour of Thermoplastic Elastomers (TPEs). These polymers are increasingly being developed as a
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on evaluating the abilities of large language models (LLMs) of replicating results from the arXiv.org repository across computational sciences and engineering. You should have a PhD/DPhil (or be near completion
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evaluations, attacks 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
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development to work under the supervision of Dr Alistair Farley, Scientific Lead for Chemistry, with a dotted line to Professor Timothy Walsh. The position is based at the Ineos Oxford Institute, at the Life
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About the role We are seeking a full-time Post Doctoral Research Assistant to join the Oxford Particles Research Group at the Department of Engineering Science (based at the Osney Thermofluids
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) information-theoretic active learning, and c) capturing uncertainty in deep learning models (including large language models). The successful postholder will hold or be close to the completion of a PhD/DPhil in
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to advance hepatitis B and liver disease research and to develop novel analytic approaches for NHS routine data. You will be based at the University of Oxford, joining a collaborative, interdisciplinary
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quality refereed journals and write reports for submission to research sponsors. You must hold a PhD (or be near completion) in a biomedical field of laboratory-based research (ideally immunology and/or
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, or computational modelling. This post is based at the Department of Computer Science and on-site working is required. Remote and part-time working options must be agreed with Professor Nobuko Yoshida. What We Offer