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statistics, applied mathematics, and/or computational science. This position is funded by EPSRC, the Met Office, and Lancaster University. Lancaster University is a research-intensive university, ranked in
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We are seeking to appoint a Senior Postdoctoral Researcher in Statistical Machine Learning and Deep Generative Modelling to apply and develop cutting- edge deep generative probabilistic models
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digital media, you will lead core research on reading and writing development using longitudinal school testing, experimental paradigms, and statistical modeling. You Will Have: A PhD (or near completion
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(awarded) in relevant subject area (e.g., epidemiology, population health, quantitative social science, statistics, psychology, neuroscience). Excellent knowledge of statistics, including statistical
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respiratory tract disease status) to translate ambient/indoor concentration data into internal dose estimates. Contribute to statistical analyses linking IAQ and human biomonitoring (HBM) data to self-reported
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the John Templeton Foundation. Gravity from Entropy is a statistical mechanics approach that derives gravity from principles of information theory and differential geometry. The aim of the project is to
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hold a relevant PhD/DPhil or be near completion* in one of the following: Finance, Mathematics, Statistics, Econometrics, Computer Science, or a closely related subject (preference will be given to those
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analytical procedures that are applied for proteome characterisation to a high degree of precision; able to analyse quantitative proteomic data with a degree of statistical rigour using common freely available
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such as multiplex proteomics. The postholder will contribute to the planning and delivery of ATLAS studies, prepare and clean large-scale datasets, apply appropriate statistical methods, and assist in
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internationally recognised research environment. It is essential that you hold, or be close to completing, a PhD/DPhil in computational biology, mathematics, statistics, bioinformatics, oncology or another related