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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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, CUDA, etc. Experience with numerical methods such as FDTD, FEM, BEM, etc. Basic knowledge of numerical linear algebra concepts, such as matrix factorization and decomposition algorithms. Familiarity with
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, or multi-physics simulation. Experience and skills · Ideally 3–5 years of experience (including PhD) in one or more of the following: o Finite Element Modelling (FEM), o Multiphysics
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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
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materials, particularly in modelling and/or testing Basic understanding of finite element methods (FEM); any exposure to impact or burst mechanics is a plus Familiarity with FE simulation tools such as ANSYS
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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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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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in Adelaide and Melbourne. Expected outcomes The Finite Element Method (FEM) is the current dominant approach for modelling real-world signals but requires substantial, uniformly distributed data. Real
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qualities and suitability. Your workplace This ELLIIT -funded project will be conducted at the Physics, Electronics, and Mathematics (FEM ) division within the Department of Science and Technology (ITN