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-speed cameras (in a newly renovated lab dedicated to our research group). A significant component of the analysis will include image processing, including data-driven methods and machine learning. You
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preferably has strong programming skills and experience with the modeling and simulations of fluid or solid mechanics or ice sheet flow and deformation (for example by use of finite element/volume methods
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utilise numerical techniques including the finite element method to describe biofluid flow and deformation in the human brain tissue. Parameters are inferred from clinical data including medical images
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experience in microstructural analyses. Familiarity with mechanical testing procedures and, ideally, experience in numerical simulation (e.g., finite element methods). Strong analytical skills, an independent
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outcomes of this research will be well-validated computational analysis methods to predict failure mode, and quantify defect and damage produced in fibre metal laminate composites. The models can be used
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Principal Investigator (PI) or Co-Principal Investigator (Co-PI) on research studies. Perform non-linear, dynamic, finite element analysis (FEA) and design for various research studies involving low- to high
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-cycle fatigue. The research methods are based on both small-scale and full-scale experimental testing and on Finite Element Modelling. Are you motivated to take a step towards a doctorate and open
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failure analysis using advanced finite element models and simulation techniques. This is enabled by digital and sensor technologies such as artificial intelligence, computer vision, drones, and robotics
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of materials mechanics, e.g., plasticity, porous plasticity, crystal plasticity and damage mechanics. Knowledge of micromechanical modelling. Knowledge of non-linear finite element methods. Knowledge of FFT
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of building and structural concepts through the development of AI-enhanced Finite Element Method (FEM) tools. It includes implementing FEM-based systems capable of proposing innovative structural forms