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apparatuses, free space and fiber optics, precision interferometry, quantum optics, analog and digital controls, low noise electronics, simulation and modeling, finite element modeling, and computer programming
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heavy software development component. The successful candidate will perform research in the application of machine learning (ML) techniques to the finite element method (FEM) in the context of composites
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Electrode Assembly. J. Power Sources 2021, 512, 230431. https://doi.org/10.1016/j.jpowsour.2021.230431. ; [2] Carral, C.; Mélé, P. A Numerical Analysis of PEMFC Stack Assembly through a 3D Finite Element
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for the project. The research will primarily involve physical modelling of Li-ion batteries through finite element methods. Requirements: PhD degree in chemistry, physics, materials science or engineering, or a
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hydrodynamic load and structural finite element model against experimental results, investigating uncertainties and sensitivities. Assess structural static and dynamic performance under 50-year return period
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structure-preserving discretization algorithms (a refinement of finite-element analysis compatible with exact geometric, topological, and physical constraints) with artificial neural networks for achieving
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mathematics. An important aspect of the ongoing research is solving stochastic partial differential equations on surfaces, e.g., with surface finite element methods. The following requirements are mandatory: A
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research area: Python or C#, robotics, additive manufacturing, finite element analysis, or computational fluid dynamics. Experience in teaching and co-supervising thesis students at university level
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working in radiological environment. Experience in heat transfer and thermal modeling/simulation using finite-element analysis (FEA) or other software. Ability to work within a multi-disciplinary team