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. This unique position combines advanced finite element modeling, machine learning, and experimental studies, while offering the opportunity to contribute to open-source libraries and collaborate directly with an
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modeling, machine learning, and experimental studies, while offering the opportunity to contribute to open-source libraries and collaborate directly with an innovative startup partner. You will be
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of numerical modelling (e.g. CFD, FEA, FSI, optimization, ML), but we are also involved in experiments and real-life monitoring to support our findings. Besides research, our division is actively involved in
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heavy-duty transport. This is an opportunity to measure, characterize, model and understand the formation of brake wear particles and ultimately reduce the health impact from urban transport. The research
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environments ensure safe operations Our activities are primarily related to the development and application of numerical modelling (e.g. CFD, FEA, FSI, optimization, ML), but we are also involved in experiments
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in fluid dynamics, turbulence modeling, CFD, and turbomachinery. Experience with CAD and CFD tools (e.g., Ansys Fluent, CFX, StarCCM+, OpenFOAM). Programming skills (e.g., Python, MATLAB). Knowledge
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to emerging digital technologies Interplay between technology development and business model evolution - how advancements in technologies reshape value creation and value capture, necessitating continous
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work. A model is to be developed to estimate the material mass breakdown for various cell designs and cell formats. The model will be validated from teardown analysis of commercial lithium-ion battery
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Join us to pioneer next-generation generative models that accelerate molecular dynamics. We seek a postdoctoral researcher to develop AI surrogates for molecular dynamics (MD), slashing
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Master’s degree in Applied Mechanics, Mechanical Engineering, or a closely related field. Strong knowledge of fluid mechanics, CFD, turbulence modelling, and structural mechanics. Understanding