160 phd-mathematical-modelling-population-modelling Postdoctoral positions at University of Oxford
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with the possibility of renewal. This project addresses the high computational and energy costs of Large Language Models (LLMs) by developing more efficient training and inference methods, particularly
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The post holder will develop computational models of learning processes in cortical networks. The research will employ mathematical modelling and computer simulation to identify synaptic plasticity
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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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concept of agents has come to the fore again, prompted by the rise of Large Language Models (LLMs) – put crudely, the idea is to use LLMs, in the sense of being powerful general purpose intelligent systems
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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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should have a PhD (or close to completion) in Physics, Planetary Sciences or Earth Sciences. It will be an advantage to have experience in remote sensing, analysis of thermal data, thermal modelling
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combine a series of interdisciplinary approaches ranging from experimental embryology and fluorescent microscopy to mathematical modelling. The lab is highly interdisciplinary and collaborative. You will
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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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language processing (large language models) to investigate the brain computations supporting planning in humans, and how this can go awry in psychosis. What We Offer As an employer, we genuinely care about our
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We are seeking a talented and motivated researcher to join the Mead Group to contribute to a major research programme focused on characterisation of in vivo models of myeloid neoplasms and