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Simon Fraser University | Burnaby (Cascade-Schou / Douglas-Gilpin), British Columbia | Canada | 9 minutes ago
outstanding research potential in scientific machine learning, numerical analysis, scientific computing, or related areas. Strong scientific computing skills are essential. Prior experience in weather
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Mathjobs.org | 27 days ago
computing and GPU acceleration. We seek applicants with a strong aptitude for research and a demonstrated ability to work at the interface of applied mathematics, scientific computing, and physics. The
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Simon Fraser University | Burnaby (Cascade-Schou / Douglas-Gilpin), British Columbia | Canada | 6 days ago
computing and GPU acceleration. We seek applicants with a strong aptitude for research and a demonstrated ability to work at the interface of applied mathematics, scientific computing, and physics. The
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analysis, scientific computing, PDE together with research experience in scientific machine learning, are particularly encouraged to apply. Required Application Materials Applications will be reviewed
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mathematical foundations and modern aspects of quantum information science, potentially including algebraic and geometric quantization, quantum probability, quantum computing, quantum algorithms for PDEs
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geometry, number theory, data. * Qin Li: Scientific computing, machine learning, inverse problems. * Hanbaek Lyu: Combinatorics, probability, optimization, and machine learning. * Laurentiu Maxim
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Mathjobs.org | 27 days ago
information and quantum computing, as covered by the section Analysis and Quantum, the Center for the Mathematics of Quantum Theory (QMATH), and the Quantum for Life Center. For more information about the above
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information and quantum computing, as covered by the section Analysis and Quantum, the Center for the Mathematics of Quantum Theory (QMATH), and the Quantum for Life Center. For more information about the above
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Mathjobs.org | 27 days ago
generative models, particularly diffusion- and flow-based models, as well as their applications to scientific computing and other scientific domains. Candidates with strong backgrounds in stochastic
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generative models, particularly diffusion- and flow-based models, as well as their applications to scientific computing and other scientific domains. Candidates with strong backgrounds in stochastic