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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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software projects Desired Qualifications: ● Experience working with large survey data (e.g., LSST, DES, HSC, Euclid, Roman) ● Knowledge of image simulation frameworks and pixel-level analysis techniques
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 16 days ago
to contribute to innovative projects at the forefront of healthcare delivery improvement, leveraging Large Language Models (LLMs) and clinical data analysis. About the Position Our Postdoctoral Research Program
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leverage the GFDL-MOM6 North West Atlantic model to perform a range of simulations under the shared socioeconomics pathways (SSP) future scenarios. Analyses will involve interpreting and analyzing large data
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experience working with large, complex data from varied sources. The candidate should have proficiency with statistical software, ideally Stata, strong written and interpersonal communication skills, and a
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making and number sense, as well as how these processes are impaired in autism spectrum disorder, using custom-built virtual reality behavioral tasks in mice. Our major approaches include large-scale in
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 days ago
to reside within a reasonable commuting distance of their assigned duty station. The Data-Driven EnviroLab (DDL) is an interdisciplinary and international research initiative based at UNC's IE that is
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candidate will participate in RNA project for structural characterization of RNA by SAXS, x-ray crystallography, and Cryo-EM. The main role for the project is to produce RNA samples in large scale by using in
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. Responsibilities Data Analysis Performs hypothesis-driven computational research with a clear understanding and use of controls. Uses computational methods to analyze large-scale sequencing data and formulate
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oceanography with demonstrated strengths in large data analysis, multivariate statistics, acoustic theory, and optical theory. The position will be primarily located in the Lewes Campus of the University