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opportunities, outdoor recreation and Big Ten sporting events. Learn more about Iowa City and the Department of Internal Medicine by watching the video: https://medicine.uiowa.edu/internalmedicine/about-us/why
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to the ongoing research in Prof. Marcotti’s laboratory by designing, developing and performing experiments, data analysis and disseminating the findings by writing articles and by presenting findings
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, creative start-ups, big data, big ambitions, hands-on learning, and a whole lot of robots, CMU doesn’t imagine the future, we invent it. If you’re passionate about joining a community that challenges the
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data and high-throughput, multi-dimensional -omic data to study neurodegeneration and diseases of the central nervous system, with an emphasis on Alzheimer disease, Parkinson’s disease, and other
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 days ago
Posting Information Posting Details Department Physics and Astronomy - 319000 Posting Open Date 08/01/2025 Application Deadline Open Until Filled No Position Type Postdoctoral Scholar Position Title
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propagation problems, stochastic partial differential equations, geometric numerical integration, optimization, biomathematics, biostatistics, spatial modeling, Bayesian inference, high-dimensional data, large
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care actually happens, and how it can be made better. This is a role for someone who’s excited to work with big, messy, real-world data — and who wants to do more than just build models. We’re looking
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modeling. Brief Description of Duties: The Postdoctoral Associate will assist the Principal Investigator Dr Fang Luo in the Department of Electrical and Computer Engineering . The incumbent will conduct
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experience in life cycle assessment (LCA) and related tools for managing large data sets to evaluate natural resources needed to advance emerging technologies. The candidate will lead their primary project and
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dynamic and collaborative research environment. Basic data science skills including the statistical analysis of large data sets. Prior experience in one or more of these techniques: design and generation