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computational resources scaling with the number of sources squared – which is inherently problematic numerically. Secondly, the differential equation used to evolve a magnetic system forward in time might be
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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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Pacific Institute for the Mathematical Sciences | Northern British Columbia Fort Nelson, British Columbia | Canada | 11 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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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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, 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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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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University of British Columbia | Northern British Columbia Fort Nelson, British Columbia | Canada | 2 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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"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
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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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; knowledge in numerical methods and simulation, particularly for partial differential equations, and basic knowledge in mathematical modeling with/and PDEs, with a focus on fluid or biomechanics, porous media