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and carry out finite element method (FEM) simulations. Our developments focus on higher efficiencies, more cost-effective manufacturing processes and materials, improved long-term stability and new
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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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systems. Experience with NQA-1 quality assurance requirements for nuclear facilities. Knowledge of AWS welding codes and standards. Familiarity with finite element analysis (FEA) software, such as ANSYS
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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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are developing AI that can map welding processes in the automotive industry based on simulation data. We are looking for a student assistant with an interest in machine learning and finite element simulation. Your
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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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fields. Solid background in geotechnical earthquake engineering, structural dynamics, and finite element modelling Experience in multi-hazard risk assessment is desirable Experience in programming (MATLAB
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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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medical image analysis. Our finite element brain models are based on tissue segmentation and our numerical simulations are validated against existing imaging data. The group’s long-term vision is to impact