39 algorithm-development-"Multiple"-"Prof"-"Prof"-"Simons-Foundation"-"U.S" Postdoctoral positions
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accurate completion. Algorithm Design: Design and implement algorithms for tensor completion, considering the unique challenges posed by sparse and multidimensional network data. This involves developing
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wide range of resources and is mostly not publicly available. While sharing proprietary data to train machine learning models is not an option, training models on multiple distributed data sources
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methods to improve the deployment, adaptation capabilities and safety of robots and critical infrastructures. The developed algorithms will be evaluated on legged robots, wheel-based robots and under
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wide range of resources and is mostly not publicly available. While sharing proprietary data to train machine learning models is not an option, training models on multiple distributed data sources
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technology and develop human resources. The AI Computing Team explores the design and realization method of advanced machine learning systems by working across multiple layers, including circuits, devices
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| Mechanical and Aerospace Engineering Perform basic research in computational fluid dynamics, including problem setup, simulation and advanced post-processing for multiple projects. Emphasis to be placed
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 hours ago
conduct advanced research in artificial intelligence (AI) and machine learning, with a focus on developing novel algorithms and systems. The position offers opportunities to work at the intersection of AI
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magnetometry measurement and analysis of the Nab spectrometer magnetic fields, help develop the BL3 DAQ and algorithms, carry out Monte Carlo simulations for Nab and BL3, and help undergraduates at EKU finish
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of the AI algorithms. Key duties Develop a robust framework to simulate streamflow decomposed into fast-flow and baseflow at multiple Moroccan watersheds. The candidate would have to test various fast-flow
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accurate completion. Algorithm Design: Design and implement algorithms for tensor completion, considering the unique challenges posed by sparse and multidimensional network data. This involves developing