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Information Geometry. (2) Computing for AI: Programming Language Theory, Algorithm Theory, Combinatorics, Optimization Theory, and Homomorphic Encryption. (3) AI for Science: Applications of Artificial
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Inference, and Information Geometry. (2) Computing for AI: Programming Language Theory, Algorithm Theory, Combinatorics, Optimization Theory, and Homomorphic Encryption. (3) AI for Science: Applications
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University, led by Prof. Melanie Weber. This role offers an opportunity to perform research at the intersection of Geometry and Machine Learning, with a focus on studying geometric structures in data and
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and proposing the fundamental principles, algorithms, and implementations for solving high-level visual perception and cognition problems involving computational geometry, automated image and video
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and proposing the fundamental principles, algorithms, and implementations for solving high-level visual perception and cognition problems involving computational geometry, automated image and video
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postdoctoral position is available in the Geometric Machine Learning Group at Harvard University, led by Prof. Melanie Weber. This role offers an opportunity to perform research at the intersection of Geometry
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multidisciplinary team, familiarity with best practices in software engineering, and efficacy at communicating and planning with computer-facility technical staff. Experience with algorithms for hydrodynamic-scale
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and Physics at Syracuse University invite applications to fill multiple faculty positions in the field of quantum information science, broadly defined. Faculty will be appointed in either
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, topology, and geometry, especially their connections to combinatorics, symbolic computation, and mathematical physics; core areas of applied mathematics, including matrix analysis, numerical analysis
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Polytechnic Institute, and Stevens Institute of Technology. Research and education areas at DIMACS include algorithms, combinatorics, complexity, privacy and security, discrete and computational geometry