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(including Applied and Computational Mathematics as well as Mathematical and Theoretical Particle Physics), and Statistics and Probability. The research culture is vibrant, with many visitors, seminars
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, and market and protocol design. The postholder should hold a relevant PhD/DPhil or be near completion in one of the following: Economics, Finance, Operations Research, Statistics, Econometrics
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techniques from statistical physics, Bayesian inference, and complex systems theory to address challenges posed by noisy and incomplete data. Depending on the results obtained in the first year, the post can
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developing characterisations of network models and interactions with methods in statistical machine learning. The post holder provides guidance to junior members of the research group including project
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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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developing characterisations of network models and interactions with methods in statistical machine learning. The post holder provides guidance to junior members of the research group including project
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University of Cambridge, Department of Pure Mathematics and Mathematical Statistics Position ID: CambUK -RESEARCHASSOCIATE [#26302] Position Title: Position Type: Postdoctoral Position Location
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challenging analyses, overcoming statistical problems, producing high-quality visualisations and outputs, and delivering reproducible analysis scripts. You also need a strong track record of delivering high
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crops and soil. Skills in environmental modelling and statistics. A positive record in scientific publication / report writing. Evidence of strong team working in research setting. Industry and
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with experimental collaboration to uncover complex biological mechanisms. Our interdisciplinary work draws on statistical physics, applied mathematics, and close ties with experimental labs. Current