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project is to develop scalable and privacy-preserving Bayesian computational algorithms. The position is intended for two to three years, with an initial one-year appointment renewable contingent upon
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computational tools, pipelines, or algorithms to improve the accuracy and speed of genomic workflows, particularly for rare variants and noncoding regions. • Functional Follow-up: Implementing functional assays
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methodologies and tools for economic and ecological analyses of hydropower systems. The position will involve the development and use of computer models, simulations, algorithms, databases, economic models, and
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Postdoctoral Researcher – AI-Augmented Decision Science Indiana University Bloomington Department of Psychological & Brain Sciences and Luddy School of Informatics, Computing, & Engineering Position Overview
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. - Strong proficiency in machine learning, optimization algorithms, and computational modeling applied to construction systems. - Experience with designing and conducting experimental studies to evaluate
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for transmission or distribution grids, synchronous generators, large loads, transmission networks, etc. Develop simulation algorithms that enable large-scale simulations. Integrate (or co-simulate) grid component
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, transportation, and more, with a special emphasis on grid resilience assessments and equity analysis. You will have the opportunity to creatively use interdisciplinary methods from computational data science
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software and high-performance computing (HPC). These include particle and gravitational physics. -On the data analysis side, the group designs novel statistical methods for particle physics and astrophysics
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 days ago
/or machine learning/artificial intelligence algorithms. Projects may also include work focused on the analysis of spatial and geographic data and work extrapolating results to different spatial scales
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are expected to have a PhD in Physics, Mathematics, Computer Science or a related quantitative discipline. Ideal candidates from the biological sciences should have experience with scientific programming. Ideal