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analysis. Experience in Finite Element Analysis software such as Ansys. Excellent communication, analytical, leadership and project management skills Further information This is a full-time role (37.5 hours
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for success: A PhD in Mechanical Engineering, Materials Science, Physics, or a related field. Experience in computational mechanics, finite element analysis, and numerical simulations. A strong background in
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to isolate geometric features of interest for further dataset curation and training Develop tools which interface between the trained predictor / inference models and structural finite element model generators
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computer aided design, finite element analysis and manufacturing software. Expertise in material science, ideally relevant to impact protection and mitigation applications. A high level of practical ability
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for downhole milling tools. Conduct Finite Element Analysis (FEA) of cutting mechanics under downhole conditions. Support design and validation of prototype tools using the company’s bespoke instrumented test
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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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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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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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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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relevant data generation, analysis, and pre-/post-processing. Knowledge of principles and techniques in computational mechanics and mechanics of materials, with a focus on finite element analysis of large