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the GOSH DRE. The postholder will have a strong foundation in statistical analysis and epidemiological approaches, and experience of analysing longitudinal data. They will join a team conducting
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• PhD in Mathematics/Statistics/CS. Skills: • Proficiency in reinforcement learning, quantitative finance, risk management, and machine learning. • Strong programming skill in Python
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, differential geometry, and/or data science. Specific topics of focus include, but are not limited to, linear response, statistical limit laws, random and nonautonomous dynamical systems, spectral analysis
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to make models realistic, and analyzing output from simulation runs using established statistical techniques. Opportunity exists for novel approaches, and you will be encouraged and supported to publish
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interacts with the human body—making it a key factor in both product performance and consumer satisfaction. You will also apply statistical and machine-learning tools to explore how cotton fiber properties
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–making it safer, more efficient, competitive, accessible and sustainable. The Fellow will be placed within one of the following OST-R offices: • Bureau of Transportation Statistics • Highly Automated
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quantitative research methodology and advanced statistical analysis, including experience with large longitudinal or population-level datasets Background in at least two of the following areas: epidemiological
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Position Description The Terhorst Lab in the Department of Statistics at the University of Michigan is recruiting a postdoctoral research fellow in statistical genetics and computational genomics
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, molecular plant virology, bioinformatics, and genomics. Collects, analyzes, interprets, and presents research data using appropriate statistical and analytical methods. Maintains accurate and complete
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such as engineering, science, information sciences, statistics, social sciences, and health. A Ph.D. in a field related to the four above topics is required by the start of the appointment. Application