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candidate will have prior exposure to modern developments in at least one of these fields: numerical analysis of PDEs (with deterministic and/or stochastic methods), Gaussian Random Fields, mathematical
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] Subject Areas: Applied Mathematics, numerical methods, simulation and modelling Appl Deadline: 2025/05/31 11:59PM (accepting applications posted 2025/02/13) Position Description: Position Description
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home of several third-party funded research projects. Through cooperation with numerous academic institutions worldwide, the Department is very well connected with the international scholarly community
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University of British Columbia | Northern British Columbia Fort Nelson, British Columbia | Canada | 22 days ago
and motivated postdoctoral research fellow with expertise in numerical analysis, numerical scientific computing (including high performance scientific computing), and finite element numerical methods
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/forschung/gruppen/numerical-analysis/research/ Typical responsibilities you can expect: Mathematical derivation, analysis, and comparison of models, methods, and simulation approaches Formal proofs, e.g
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Fritz Haber Institute of the Max Planck Society, Berlin | Berlin, Berlin | Germany | about 15 hours ago
materials with applications in heterogeneous catalysis, energy conversion and electrochemistry. By combining unique synthesis methods, state-of-the art tools for experimental characterization and advanced
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institutions, and a research and development provider for numerous companies throughout the world. The INM is a member of the Leibniz Association and has about 250 employees. The INM Research Department Energy
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performance computing numerical methods in our state-of-the-art open source micromagnetic model, MagTense. MagTense is based on a core implemented in the Fortran programming language, and it relies
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existing theories and methods. They will assist the supervisor in the interpretation and publication of results and grants. Furthermore, it is expected that they exercise functional supervision over
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, including hybrid simulations coupling machine learning with numerical methods, multiscale discretization, nonlocal closure modeling, structure preservation, multilevel and multifidelity machine learning