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testing and computational modelling. You'll become part of a diverse, multidisciplinary team that prioritises equity, diversity, and inclusion, gaining specialist expertise in hydrogen-material interactions
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at international conferences and build a professional network across academia and industry. Development of expertise in cutting-edge experimental techniques, computational modelling, and interdisciplinary
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access to cutting-edge computational tools and interdisciplinary collaboration. This is a self-funded PhD, open to both UK and international students, offering the opportunity to lead an ambitious project
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to encourage an effective and vibrant research culture, founded upon the diversity of activities and knowledge. A tailored programme of seminars and events, alongside our Doctoral Researchers Core Development
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requirements A minimum of a 2:1 first degree in a relevant discipline/subject area (e.g. aerospace, automotive, mechanical, electrical, chemical, computing, and manufacturing) with a minimum 60% mark in
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Advances in computing, experiments, and information will continue to reshape engineering in the next decade. This PhD position will nurture a multidisciplinary innovator with the tools to unravel
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
computing facilities. The Centre supports research in digital twins, knowledge-based systems, AI, and immersive technologies such as VR and AR. The candidate will work independently and collaboratively with
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supervisor/s within the theme are recognised. This is a 12 month, 100% research programme where you will achieve your MSc degree by developing a desk/laboratory/field based novel research project. Our current
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carried out at Cranfield in the continuity of what is done by considering the new experimental developments. For these CFD studies, numerical tools and super computers at Cranfield and Loughborough will be
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This PhD project offers a unique opportunity to delve into the complexities of free-market systems and sustainability through a novel ensemble prediction model. With a focus on addressing uncertainty and limited data availability, this research aims to revolutionize decision-making in...