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or physics or applied mathematics with outstanding grades Excellent knowledge of continuum mechanics and finite element analysis Excellent coding skills Knowledge and experience with fracture and/or
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and written. Solid skills in computer programming (Python / Matlab). Experience with CAD and CAE tools. Knowledge of computational fluid dynamics (CFD). Knowledge of finite element method (FEM
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. Preferably, you have experience in one or more of the following fields: scientific instrumentation, microfabrication, 3D-printing, finite element analysis, atomic force microscopy (AFM), microfluidics, optical
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or an equivalent qualification. For all posts, applicants should also: (a) have solid experience in electric machines, finite element methods and theory of electromagnetic files; and (b) be able to complete
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of computational fluid dynamics (CFD). Knowledge of finite element method (FEM). Meritorious: It is also an advantage if you have experience with: Machine learning. Coupling algorithms of fluid-structure interaction
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simulation techniques based on finite element and multibody dynamics formulations. Your tasks involve developing new elements tailored to the multi-physical effects seen in high-performance mechatronics
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skills. You’ll have strong skills in Finite Element Analysis (e.g. Abaqus, ANSYS), an understanding of machining processes, and a proactive, collaborative approach to problem-solving. The University
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methods (e.g., AFM, Nano-IR, STM, SECCM, SICM, SECM), advanced light and electron microscopy, materials synthesis (e.g., conductive metal-organic frameworks, 2D/hierarchical structures, nanoparticles
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are developing AI that can map welding processes in the automotive industry based on simulation data. We are looking for a student assistant with an interest in machine learning and finite element simulation. Your
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skills include: Interest or background in composite materials, particularly in modelling and/or testing Basic understanding of finite element methods (FEM); any exposure to impact or burst mechanics is a