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30th April 2025 Languages English English English The Department of Structural Engineering has a vacancy for a PhD Candidate in AI and FEM Development for Autonomous Structural Design Apply
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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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Using finite element modelling (FEM) to simulate different hole configurations and validating these models with cadaveric femur specimens, this study will provide crucial insights to optimise
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acquisition and statistical methods is an advantage. Experience with numerical simulations (FEM). You must have a two-year master's degree (120 ECTS points) or a similar degree with an academic level equivalent
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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
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methods/simulations, state-of-the-art computational techniques (e.g. data-driven methods and/or FEM) and/or theoretical material modeling will be given preference We offer: chance to collaborate with
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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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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