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journals and conferences. This role provides a unique opportunity to work with the world’s first exascale system, Frontier, and collaborate with leading experts in machine learning, optimization, electric
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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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significant mathematical and computational background to learn and develop new AI methods. While demonstrated experience in computer vision and deep learning for pathology or other biomedical image analysis is
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within a few months), for example in economics, social science or related field Excellent mathematical and analytical skills from fields such as mechanism design and optimal taxation Familiarity
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base, the partnership will bring together the University of Oxford’s expertise in statistics, mathematics, engineering and AI with industry scientists. Within the partnership, small research teams will
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to optimize lab-specific protocols and run the protocols at a larger scale for prototype testing. The candidate is also expected to perform the biological testing detailed in the aforementioned protocols in
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algorithms to develop cybersecurity, optimization, and control solutions for real-world grid applications. Candidates will be required to work in at least 4 of the following areas: Build, simulate, and
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on an optical table and integrating novel optics to microscopy are a requirement for this position. Knowledge in computational imaging, mathematical modeling, strong computer programming skills in MATLAB and/or
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Applied Mathematics and Plasma Physics (T-5) group at Los Alamos National Laboratory is seeking qualified Postdoctoral Research Associates. You will complete research projects on various potential topics
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Johansson. Professor Johansson works at the interface of research and operational public health using statistical and mathematical models to improve surveillance, prevention, and control of infectious