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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
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computer programs to design experimental paradigms, analyse data and conduct advanced statistical analysis. Prior experience in running neuromodulation studies including TMS and TUS is essential. You will be
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analysis) and tumour cell injection (Desirable) Experience of using bioinformatics software and methodologies to analyze multi-omic and therapeutic datasets (e.g. R statistical environment) (Desirable
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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