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Field
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. In the ELUD research project, we address the question of if and when learning agents converge to an efficient equilibrium and when this is not the case. ELUD will design new algorithms for computing
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months 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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to guarantee user-defined error bounds of reachable sets for nonlinear and hybrid systems. This project will exactly close this research gap: We will develop essentially new methods to ensure that algorithmic
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· database extraction · data cleaning · analysis · algorithm development and implementation · data visualization [CI1] The postdoctoral
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algorithms, and prototypical systems controlling complex energy systems like buildings, electricity distribution grids and thermal systems for a sustainable future. These systems coordinate distributed
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the team with compiling and analyzing geospatial datasets, developing and testing deep learning algorithms for complex image classification, optimizing data collection strategies for unmanned aerial vehicle
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imbalanced cross-sectional imaging data are especially well-suited for the position . The postdoctoral researchers will develop algorithms for deployment at our prestigious R Adams Cowley Shock Trauma Center
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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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for postdoctoral researcher position to conduct collaborative research aimed at the development of novel data mining algorithm to neuroimaging, genetic, and clinical data for brain disorders such as
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work is robustly extending genomic discoveries into under-represented populations, as well as improving portability of genetic risk prediction algorithms into the same populations in anticipation