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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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experimentally investigated. About you You should possess a PhD or DPhil (or be near completion of) in the field of engineering, physics or applied mathematics together with relevant experience in the field
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these processes, with the aim of understanding how ageing promotes CH progression. You will hold a PhD within the area of molecular biology or have thesis submitted at time of application, and will have experience
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close to completing, a PhD/DPhil in cell biology, molecular biology, biomedicine, or a related field. You will have in-depth knowledge and experience in the cell and molecular biology of cancer, as
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but part time working would be considered (minimum of 4 days, 30 hours per week, 0.8 FTE About You To be considered for this position you should have a PhD degree (or be near completion) in a relevant
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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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working under the supervision of Prof Wooldridge. Candidates will be expected to have a PhD (or be close to completion) in a related area. The primary selection criteria will be relevant research experience
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with experimental biologists to validate the hypotheses, and advise and supervise computational staff and students. You will write research articles and present the results at national and international
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will be required due to regulated activity involving children and ‘at risk’ adults. The successful candidate will hold, or have submitted a relevant PhD/DPhil (or equivalent) in a relevant discipline
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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