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Field
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, groundwater flow simulation, and numerical model development Basic knowledge of numerical methods for solving nonlinear systems of partial differential equations (e.g., finite volume method, finite element
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, preferably involving fluid mechanics and/or microstructure related simulations. Experience with numerical simulations based on the finite element method (FEM) or the finite volume method (FVM). Experience with
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computing environments. Experience with numerical modelling techniques, such as finite difference, finite element, or spectral element methods. Interest in inverse problem formulation and solving and/or
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numerical approach The PhD is part of a Franco-German co-funded project between IFP Energies Nouvelles (IFPEN) at Lyon and the Hamburg University of Technology (TUHH), focusing on the modelling of gas/liquid
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modeling to create a predictive tool that spans orders of magnitude in length and time. Hands-On Numerical Modeling: Implement your model in a custom-made data analysis tool that uses advanced optimization
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finite-difference resolvent solver incorporating stabilising filters as well as a domain-decomposition strategy suitable for complex geometries, - Use efficient time-integration methods to compute
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 3 days ago
will perform numerical simulations using particle-in-cell codes to study collisionless shock waves. The goal is to identify how the electromagnetic field structure at the shock and the spectrum
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Science, Computer Science, or a related disciplines. The candidates should have: A solid theoretical background in their field Strong programming skills and experience with numerical methods. Proven
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of numerical methods for solving nonlinear systems of partial differential equations (e.g., finite volume method, finite element method) Experience with open-source CFD software such as OpenFOAM, PFLOTRAN
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scarce settings where FM training is not feasible, prompting the exploration of synthetic data generation via direct PDE solvers. This PhD will examine how probabilistic numerical methods can enhance