155 phd-mathematical-modelling-ecological-modelling Postdoctoral positions at University of Oxford in Uk
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systems modelling including technical knowledge (e.g., in data science, input-output modelling, applied economic modelling, environmental and ecological assessments, GIS, comparative risk assessments), as
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and optimising assays aimed at target validation; principally through immunogenicity assays in animal models. You will also conduct experiments aimed at understanding the tumour-immune microenvironment
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cancer progression, immune evasion, and therapeutic resistance. We place a strong emphasis on the use of spatial biological approaches applied to human tumour models including organ/tumour perfusion, slice
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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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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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to the 4th February 2026. You will be investigating the safety and security implications of large language model (LLM) agents, particularly those capable of interacting with operating systems and external APIs
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level of detail extracted from these experiments. As part of this role, you will work closely with other researchers to translate these experimental results into our numerical models, helping to improve
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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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Leedham (colorectal cancer biology), Dan Woodcock (cancer genomics), Helen Byrne (mathematical modelling), and Jens Rittscher (computational pathology and imaging AI), offering a unique opportunity to work
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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