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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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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day 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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across AI, incorporating insights from algorithm development, systems engineering and architecture, human psychology, sociology, law, science and technology studies, economics, and policy studies. Faculty
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across AI, incorporating insights from algorithm development, systems engineering and architecture, human psychology, sociology, law, science and technology studies, economics, and policy studies. Faculty
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complex multiphysics problems. The coupling is done across package boundaries. This also requires more sophisticated approaches in load-balancing. Finally, the newly developed algorithms will be tested and
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good results - Interest on topics around the area of distributed systems and data management - Basic knowledge in distributed systems and graph algorithms is desired - Hand-on experience with large-scale
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interdisciplinary cooperations with partners and stakeholders from different domains. Candidates should have completed their Doctoral studies in Computer Science, Mathematics, Mechatronics, Electrical Engineering or