167 phd-mathematical-modelling-ecological-modelling Postdoctoral positions at University of Oxford
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Institute). The position is fixed term for 36 months and will provide opportunities to work on aircraft icing modelling and experimental campaigns. Ice crystal icing is one of the least well characterised
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an available option. Applicants with a range of academic subject backgrounds are welcomed, including natural sciences, epidemiology, engineering, statistics and applied mathematics with experience and
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developing new optogenetic treatments for inherited retinal diseases. We are looking for highly qualified individual (PhD/DPhil) with outstanding academic credentials, who can work well under pressure and
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-certification, and redeployment, as well as social acceptability and policy design. About you You should hold a relevant PhD/DPhil, or be near completion, in electrical engineering, economics, applied mathematics
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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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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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base, the partnership will bring together the University of Oxford’s expertise in statistics, mathematics, engineering and AI with industry scientists. Within the partnership, small research teams will
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, and enabling data-driven improvements in patient care. You will have opportunities to apply foundation models—including large language models (LLMs) to real-world clinical data. You will work with well
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(LiB’s). You will be responsible for: • Developing models and simulations of the electrode fabrication process, sensors, and actuators. • Developing a demonstrator of a soft sensing system that
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Claudia Monaco’s research group at the Kennedy Institute of Rheumatology. In this role, you will apply single cell biology and cell signalling techniques combined with in vivo and in vitro models