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material models based on advanced ML methods, and to seamlessly integrate these models into Finite Element Modelling (FEM) to replace expensive and time-consuming experimental procedures, thereby enhancing
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computation, with potential links to hydrogen engine research and broader digital twin technologies. You will gain expertise in: Computational modelling of materials (e.g., FEM, crystal plasticity, or phase
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material models based on advanced ML methods, and to seamlessly integrate these models into Finite Element Modelling (FEM) to replace expensive and time-consuming experimental procedures, thereby enhancing
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systems”, coordinated by Prof. Dr. Marco Salvalaglio and Prof. Dr. Axel Voigt and funded by the German Research Foundation (DFG). The core activities will focus on the investigation of disordered correlated
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models through specific activation functions. This project will be undertaken in collaboration with Dr Hemanth Saratchandran and Prof Simon Lucey of the Australian Institute for Machine Learning, and
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Some experience with numerical simulations such as the Finite Element Method (FEM) and Multi-Body Simulation (MBS) is a plus. We offer: a fascinating understanding at mobility in general with a