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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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will involve a combination of simulation and statistical modelling. Your key responsibilities will be: Lead analysis of State response data to estimate detection, occupancy, and spread of PSHB Engage
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an initially solid-like state firsts yields and starts to flow, and in particular on the statistical physics of how initially sparse plastic events in an otherwise elastic background then spatio
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support staff, and allied faculty researchers. Uses computers and technical equipment to perform data analysis, statistical analysis, and technical evaluation of air quality, weather, and related data
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methods of data analytics (e.g., statistics, stochastic analysis, Bayesian statistical analysis), physically-based hydrology and water quality models, and the use of machine learning tools for modeling flow
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interdisciplinary, and together we contribute to science and society. Your role We seek a highly motivated bioinformatician or computational biologist who is well versed in the statistical and machine learning
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for duties undertaken remotely. Required Qualifications: A PhD degree in Biostatistics, Statistics, Computer Science or a related field who possess STRONG computing/programming and communication skills
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PhD or equivalent qualification in computer science, statistics, mathematics, physics, and/or engineering, or a degree in biological science with demonstrated experience in computational and statistical
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that will be affiliated with one of six possible multidisciplinary projects. The ideal postdocs will have expertise in some of the following areas: computational modeling, computational biology, computational
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biomarkers. The successful candidate must have strong grounding in statistics. This position will focus on intensive research training, professional development and mentorship of undergraduate and graduate