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are looking for: a highly motivated researcher with at least 3 years of research experience (possibly as part of the PhD) in a field related to mathematical analysis of partial differential equations (PDEs
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conjecture, -- Langlands program and related problems, -- algebraic geometry and complex geometry, -- partial differential equations and in particular Navier-Stokes equations, -- stochastic analysis
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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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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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, 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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"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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; 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
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differential equations, computational fluid dynamics, material science, dynamical systems, numerical analysis, stochastic analysis, graph theory and applications, mathematical biology, financial mathematics
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architectures and training algorithms, uncertainty quantification, high-dimensional stochastic systems and high-dimensional partial differential equation systems. Multiple positions available. About the T-5 Group
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/or their active counterparts. • To perform direct numerical simulations of the continuum partial differential equations of fluid dynamics, solid mechanics, soft matter or active matter