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functional theory) and high-performance computing. Additional background in renewable energy, surface science, catalysis, and/or machine learning. Strong programming skills in Python and some exposure to
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environments, specifically Computer Vision, Machine learning algorithms and methods for rock characterization, fragmentation prediction, and mining optimization. Specific Requirements Good academic and
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to numerical methods for kinetic equations. Mathematical topics of interest include high-dimensional approximation, closure models, machine learning models, hybrid methods, structure preserving methods, and
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to Computational Methods for Data Reduction. Topics include data compression and reconstruction, data movement, data assimilation, surrogate model design, and machine learning algorithms. The position comes with a
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 13 days ago
with Computer Vision and Deep Learning architectures (CNNs, RNNs, etc). Strong foundation in machine learning and data science. Programming skills with proficiency in Python, Java, and/or R. Preferred
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 hours ago
with Computer Vision and Deep Learning architectures (CNNs, RNNs, etc). Strong foundation in machine learning and data science. Programming skills with proficiency in Python, Java, and/or R. Preferred
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, including artificial intelligence, machine learning, data sciences, algorithms, databases, cloud computing, software engineering, networking, operating systems and security. Job Description The successful
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About the Opportunity The Center for Drug Discovery, in association with the Bouve College of Health Sciences, Department of Pharmaceutical Sciences, Khoury School of Computer Sciences, and
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concepts; mathematics; written and computer documentation; data utilization, problem solving, critical thinking, and writing skills. Skills and abilities: Basic biochemistry techniques including but not
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working at the intersection of computer vision, and 3D AI for the built environment. Our goal is to transform how physical environments and infrastructure are captured, analyzed, and monitored using