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stimulation, and application of pharmacologic compounds during patch clamp experiments. Maintaining the electrophysiology rig, keeping accurate records of experiments, performing data analysis, and creating
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 1 hour ago
scholar to conduct in-depth analysis of stratospheric data, using data from the Microwave Limb Sounder (MLS) as well as complementary datasets like the Atmospheric Chemistry Experiment Fourier Transform
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of the research, contributing to protocol writing, and helping to oversee the execution of the research. The postdoctoral scholar will also contribute to data analysis and write-up of scientific findings
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Fellow with a PhD in Computational Biology, Bioinformatics, Biostatistics, Data Science, or a related quantitative field to join an interdisciplinary research program focused on Alzheimer’s disease (AD
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
modeling of large-scale dynamics in networks. This role involves creating large scale models of dynamic phenomena in electrical power networks and quantifying the risk of rare events to mitigate
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. Applicants must have experience in the handling and organization of large data sets. Familiarity with analysis of panel or longitudinal data and working with multilevel models is valued. Additional skills with
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large amounts of geospatial training data to effectively classify grazing, haying, and other grassland management regimes on U.S. agricultural lands. The researcher will also work closely with colleagues
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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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/Statistics Internal Number: JR101137_1774276539 The Data Science and Statistics Program at the University of Richmond invites applications for a two-year postdoctoral research position in the Distant Viewing
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scalability studies to identify and improve bottlenecks in large codes. Experience in development of data-driven reduced-order models in one or more of these areas: turbulence, boundary layer flows, combustion