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the forefront of numerical analysis for Partial Differential Equations, enriched with data-driven methodologies -- a powerful combination that’s redefining what’s possible in computational science, and is playing
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Zhennan Zhou's primary research interests lie in the applied analysis of differential equations and stochastic models, as well as the design and analysis of numerical methods for scientific problems
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work on optimization and optimal control related to partial differential equations with emphasis on new developments related to machine learning and data science. Your profile: • Doctorate related
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
mathematics, or a related field Candidates should have expertise in two or more of the following areas: Uncertainty quantification, numerical solutions of differential equations, and stochastic processes
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Pacific Institute for the Mathematical Sciences | Northern British Columbia Fort Nelson, British Columbia | Canada | 28 days ago
in the following areas but are not limited to: Structure-preserving spatial and/or temporal discretizations for differential equations Structure-preserving machine learning methods Applications
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, or a closely related field with expertise in one or more of the following areas: Finite element methods for partial differential equations Multiscale numerical methods Flow and transport in porous
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University of British Columbia | Northern British Columbia Fort Nelson, British Columbia | Canada | 3 months ago
for partial differential equations (PDEs). The Fellow will be responsible for designing, developing and implementing highly efficient, robust and stable numerical methods for mechanobiochemical models
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ecological systems with frequency-dependent selection. Planned projects use dynamical systems, stochastic differential equations and agent-based models, statistical methods for parameter inference, network and
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propagation problems, stochastic partial differential equations, geometric numerical integration, optimization, biomathematics, biostatistics, spatial modeling, Bayesian inference, high-dimensional data, large
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"Mathematical Data Science" research group at the University of Vienna (led by Prof. Dr. Philipp Grohs) and the "Computational Partial Differential Equations" research group at TU Wien (led by Prof. Dr. Michael