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website: https://www.hortenseleferrand.com/ We are looking for a researcher able to carry FEM simulations of reinforced composites materials using Abaqus. The experimental characterization of samples
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and carry out finite element method (FEM) simulations. Our developments focus on higher efficiencies, more cost-effective manufacturing processes and materials, improved long-term stability and new
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develop new computational methodologies and associated software framework under the guidance of the PI and other collaborators in the project. Your strong working knowledge of numerical methods such as FEM
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and active‑heating rigs; Strong programming skills (Python/Matlab and/or FEM packages); Publication record appropriate to career stage; Excellent teamwork, project‑management and communication skills
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to join an ambitious research project on representation and public opinion. Read more about the position and apply here . The research project The position is part of the project “Fem-LEAD: Female Leaders
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-time data acquisition during production, consulting, and prototype manufacturing. Graph neural networks provide an opportunity to operate on Mesh structured data utilized in Finite Element Method (FEM
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mechanics, numerical methods (BEM and FEM) computing skills (e.g. C++, Python, ... ) good knowledge of the English language Admission Requirements Engineering diploma (Dipl.-Ing.), Master of science (M.Sc
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methods (FEM/FVM) and scientific computing Proficiency in Julia, C++, or Python and experience with HPC environments Interest in geophysical applications, fracture modeling, or multiphysics simulations
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; · Solid background in power electronics and magnetic component design; · Experience with modelling and simulation tools (such as MATLAB/Simulink, FEM software like COMSOL or ANSYS Maxwell
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powders Skills: FEM software (Comsol Multiphysics, Abaqus), CAD software (Solidworks, AutoCAD), UNITY3D, Visual C++, LabVIEW We regret to inform that only shortlisted candidates will be notified. Hiring