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plus Familiarity with FE simulation tools such as ANSYS or Abaqus (or willingness to learn) General knowledge of structural analysis and material behaviour, especially failure mechanisms Some experience
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of innovative computational methods using Big Data, Behavioural Science and Machine Learning to understand behaviour through the lens of digital footprint/“smart data” datasets, cutting across sectors ranging
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with competitive employment packages, discounted access to fitness and health facilities, a generous holiday allowance and an attractive pension scheme; visit the Your Benefits website to learn more
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of GAGs Are confident working with complex data Enjoy learning beyond your current expertise with the support of our excellent interdisciplinary team Eligibility Start date: 1 October 2025 Open to
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cohort to benefit from peer-to-peer learning and transferable skills development. For full information about the programme, the research projects available and how to apply, please visit: http
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into hydrogen and nitrogen under practical onboard conditions. Successful candidate will develop and apply computational methods, such as density functional theory based atomistic modelling and machine learning
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between chemical and mechanical aspects of sperm cell biology remain largely unknown. In this project a successful candidate will learn, elasticity characterisation techniques, processing and evaluation