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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Dresden, Sachsen | Germany | 20 days ago
algorithms for solving partial differential equations # Implementation, testing, and benchmarking of computational methods on high-performance computing and quantum computing platforms # Analysis and
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%29-Partial-Differential-Equations-2628-CD/1353903857/ . Contact: Emiel Lorist Email: Postal Mail: * Web Page: https://www.tudelft.nl/en/eemcs/the-faculty/departments/applied-mathematics/
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for Postdoctoral Associate positions in the broad research areas of mathematical analysis and partial differential equations (PDEs). While all applicants with a background in the analysis of PDEs will be considered
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 18 days ago
), financed by national funds through FCT Workplan: The candidate(s) will have experience in mathematical modeling and programming for nonlinear Ordinary and Partial Differential Equations. He/she will study
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. The advertised position will be placed at the Division of Applied Mathematics. The division conducts broad research in applied mathematics, with an emphasis on numerical analysis for partial differential equations
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, United States of America [map ] Subject Areas: Calculus, Differential Equations, Statistics Appl Deadline: (posted 2025/08/26 05:00 AM UnitedKingdomTime, listed until 2026/05/01 04:59 AM UnitedKingdomTime) Position
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simulation, with formal training or demonstrated experience in: Quantitative Systems Pharmacology or differential equation-based mechanistic modeling Ability to translate biological hypotheses
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areas will be considered when selecting candidates: Machine Learning, Neural Networks, Numerical solutions of Partial Differential Equations and Stochastic Differential Equations, Numerical Optimization
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learning, with a particular focus on differential equation-driven frameworks. The research will be fundamentally oriented, and the overall mission is to develop computationally efficient and statistically
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approaches. Through innovative work combining machine learning with new paradigms for direct solvers of high-dimensional partial differential equations, members of CHaRMNET aim to overcome this challenge