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for metric-valued (including functions, distributions) data analysis, optimal transport and gradient flows, and deep learning. A Ph.D. in Statistics, Mathematics, CS/EE (with a focus on statistics/machine
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. We are seeking a Postdoctoral Researcher to join the team and make significant contributions to the field. The researcher is expected to have (i) strong machine learning skills to improve model
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future. Fueled by curiosity and a deep sense of duty, they contribute invaluable insights to research and teaching, enriching our society. Are you inspired and driven by the desire to make a meaningful
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and correct skills to continuously operating robots. Job description We are seeking a postdoctoral researcher for a 2-year contract to advance robot learning in shared control with a human operator. The
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Electrical Engineering, Computer Science, or a related field Strong background in speech processing, signal processing or machine learning Proficiency in Python and deep learning frameworks Experience with far
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ethical frameworks. Proficiency in Python and experience with relevant libraries for AI/ML development. Experience with advanced AI methodologies including deep learning, transfer learning, and neural
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Internal Number: 6397400 Postdoctoral Scholar - Voting Law/Data Analysis- Goldman School of Public Policy Position overview Position title: POSTDOC-EMPLOYEE Salary range: The UC postdoc salary scales set the
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at the intersection of AI/deep learning, bioinformatics, mathematical modeling, computational topology, scientific machine learning, for systems biology, single-cell genomics and protein design. The candidates will
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postdoctoral researcher for pioneering research at the convergence of artificial intelligence (AI) and materials science. The ideal candidate should possess expertise in scientific machine learning (SciML
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ophthalmological, neuroimaging and behavioral data, and incorporate deep learning methods to facilitate biomarker discovery and enhance predictive power. As a postdoctoral associate you will join a multidisciplinary