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research focuses on a geometric understanding of training in deep neural networks. The position offers excellent training opportunities at the intersection of machine learning and applied mathematics
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University of California, Berkeley, Department of Electrical Engineering and Computer Sciences Position ID: University of California, Berkeley -Department of Electrical Engineering and Computer
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geometric understanding of training in deep neural networks. The position offers excellent training opportunities at the intersection of machine learning and applied mathematics. Qualifications: - Applicants
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, California 95616, United States of America [map ] Subject Areas: Physics / Astronomy , Astrophysics Computational , Machine Learning Salary Range: Starting at $71,491/year or higher depending on experience
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, particularly on measurements and searches using jet substructure and development of advanced techniques in particle tagging, including applications using machine learning, and are expected to take leading roles
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University of California, Berkeley, Department of Electrical Engineering and Computer Sciences Position ID: University of California, Berkeley -Department of Electrical Engineering and Computer
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be well supported by a community of postdocs and resident researchers. You will have access to our Learning Hub trainings and other resources for professional development. Your proposed independent
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practices ● Fluency in programming languages such as R and Python. ● Demonstrated ability to make reproducible code for cleaning, integrating, and modeling spatial/temporal data from multiple sources, spatial
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times. The successful candidate will contribute to current data analysis efforts in the group, which focuses on Higgs-boson physics and searches for new physics beyond the standard model. Postdocs in
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, work independently, learn new skills, and contribute positively to departmental culture. The department is especially interested in candidates who can contribute to the diversity and excellence