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of computational fluid dynamics (CFD). Knowledge of finite element method (FEM). Meritorious: It is also an advantage if you have experience with: Machine learning. Coupling algorithms of fluid-structure interaction
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skills. You’ll have strong skills in Finite Element Analysis (e.g. Abaqus, ANSYS), an understanding of machining processes, and a proactive, collaborative approach to problem-solving. The University
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printing, rapid prototyping, Finite element analysis (FEA), Multiphysics analysis, Design for composite materials, material science Preferred skills/experience areas include: Finite element analysis
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loading conditions. Finite Element models of the designed specimens will also be generated and biomechanical behaviour of the tooth restored complex will be predicted. Supervisors Prof Hassan Ghadbeigi
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and accelerated brain aging by coupling mechanics and neurobiology to create multiphysics-informed predictive models of brain health. Specifically, our approach combines finite element modelling and
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characterisation of carbon fibre composites, spanning temperatures from room temperature to liquid hydrogen temperature (20K). Development of a finite element model of carbon fibre composites to incorporate rate and
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sizing, and relief device sizing. Experience withpractical finite element analysis using ANSYS Workbench or Comsol, and pipe stress analysis programs such as CAESAR-II, CAEPIPE, AUTOPIPE, WINPIPE, ROHR2
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to plasticity. (assessed at: application/interview) Experience in computational mechanics, especially numerical methods for solving field equations relevant to material mechanics, i.e., Finite Element schemes
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in finite element modeling with Ansys Mechanical, APDL, and Discovery. You possess very good programming skills in Python. You work independently and in a structured manner. You are reliable, flexible
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have an excellent PhD in biomechanics (or a related discipline), possess a solid knowledge of non-linear finite element modelling, have a strong experience in developing and validating patient-specific