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Field
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built in the commercial finite element software ‘Abaqus’ to capture pellet clad interaction in both light water reactors (LWRs) and the UK advanced gas cooled reactor (UK-AGR). Whilst Abaqus offers
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structural health monitoring and simulation. Good written and oral communication skills Proficiency in ABAQUS, and lab test skill Ability to work independently and develop solutions under strict timelines We
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models and their implementation (such as in FEniCS/FEniCSx and in Abaqus via user-element and user-material subroutines (UEL/UMAT)), preparing manuscripts for peer-reviewed journals and presenting results
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interpretation of structural response and failure modes. Develop, calibrate and validate nonlinear finite element models in ABAQUS, incorporating material strain hardening, geometric imperfections and realistic
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Python programming, gaining valuable research experience alongside your studies. You will collaborate with an experienced, interdisciplinary research team and contribute to the development of Abaqus
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to work independently to develop Abaqus of metallic kirigami and develop reduced-order analytical models to understand and describe observed behaviour. They will also be expected to contribute to writing
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civil engineering or related field. At least 1 year of relevant experience in machine learning and structural health monitoring. Good written and oral communication skills. Proficiency in ABAQUS, and lab
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• Finite element analysis using MOOSE and ABAQUS • Constitutive models of asphalt binder and mixture, balanced mix design and pavement engineering • Drone surveying using LiDAR and photogrammetry
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communication skills Proficiency in ABAQUS, and lab test skill Ability to work independently and develop solutions under strict timelines We regret to inform that only shortlisted candidates will be notified. Hiring
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and at most 17 hours. Be part of change CAE modelling and numerical simulation (e.g. sheet metal forming processes using ABAQUS, etc) Develop data-driven and machine learning-based models to improve