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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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publication Strong programming skills and familiarity with machine learning or finite element modelling Not currently receiving another scholarship of equal or higher value Application process Future student
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finite element and ray tracing techniques Experience with optical and electrical characterisation Experience with fabrication of light management structures (e.g. AR coatings, Bragg reflectors, photonics
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below, attaching as a separate document: Essential A PhD in materials science, photovoltaics, photonics or a closely related discipline Expertise in optical modelling using finite element and ray tracing
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finite element methods, which demand extensive data and are costly, PINNs embed governing physical laws directly into the learning process. This allows effective management of limited and noisy data
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process. About You Completion or near completion of a PhD in geophysics. Background/skills in finite element numerical modelling, geophysical Inversion theories, optimisation and parallel computing. Skills
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Australia. Knowledge and background in solid mechanics and Finite element analysis will be beneficial to undertake this project. Residual strength degradation and fatigue behaviour of composite laminates
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this position, you will have: PhD degree in relevant field Demonstrated knowledge of structural analysis of alloy components, Finite Element Modelling (FEM) and preferably morphology/topology optimisation
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techniques and associated tools (examples include, but are not limited to machine learning, density-functional-theory, materials informatics, finite-element modelling, phase-field modelling), and demonstrated
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) + Finite element methods for complex flows in porous media (generalized multiscale finite elements via autoencoders, adaptive in space and time, splitting methods, and variational flux recovery) + Adaptive r