78 modelling-complexity-geocomputation Postdoctoral positions at University of Oxford
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renewable award. You will lead a programme of research in the molecular mechanisms of cardiovascular disease, that may include a range of approaches including targeted genetic murine models, primary cell
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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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work with in vitro and in vivo models of genetic diseases would be advantageous. Please see the below 'Job Description' for further details on the role, responsibilities, and selection criteria, as
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structural), ECG, and genetics, to model disease trajectories and improve risk prediction in cardiomyopathies. The successful applicant will work closely with the PI to deliver research projects, supervise
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human tumour models including organ/tumour perfusion, slice culture and organoids to ensure data is clinically relevant and to inspire the next generation of effective treatments. The post would suit
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/weather observational and modelling products would be of a substantial value. Furthermore, experience with epidemiological modelling and/or attribution of extreme events and their impacts in a changing
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Haematology Unit. You will use state-of-the-art genetic tools and functional genomics to generate and characterize models of CH and ageing, including the role of the bone marrow microenvironment in
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structural maintenance of chromosomes (SMC) complexes shape chromosomes by DNA loop extrusion, how they cooperate with DNA topoisomerases, and how bacteriophages and other infectious agents manipulate host
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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
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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