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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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in the Mathematical Institute (https://www.maths.ox.ac.uk/groups/mathematical-biology/infectious-disease-modelling). The postdoctoral researchers will develop data-driven mathematical models and
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Machine Learning, Human-Computing Interactions, Social Sciences, and Public Health. Applicants should hold, or be close to completion of, PhD/DPhil with research experience in computer science, statistics
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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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Engineering, Mathematics, Statistics, Computer Science or conjugate subject; strong record of publication in the relevant literature; good knowledge of machine learning algorithms and/or statistical methods
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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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data from a variety of sources, including Spatial Transcriptomics and multiplex Spatial Proteomics platforms and developing skills in computational biology and mathematical spatial analysis via
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in Python, or demonstrated ability to rapidly acquire fluent knowledge of new programming languages, libraries, and platforms. A background and/or interest in mathematics or computer science would be
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at the Mathematical Institute, University of Oxford. This is a 15-month fixed term position, until 30 September 2026, though it may be extended if additional funding is forthcoming. The successful candidate will be
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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 or another related area. (For