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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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‘Apply’ button. Under programme name, select *School of AACME*. Please quote the advertised reference number: * MP-SH-2504* in your application. To avoid delays in processing your application, please
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(£20,780 for 2025/26). How to apply: To apply click Apply for a Programme via the above ‘Apply’ button, create your account, and use the link sent by email to start the application process. Please select
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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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technologies, neurodegeneration models, and interdisciplinary collaboration. This is an exciting opportunity to contribute to a growing research programme with the potential to lead to PhD study or further
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Research Assistant/Research Associate* in Cardiovascular Epidemiology (BHF Scholarship) (Fixed Term)
be considered. As a group, we value and encourage applications from a diversity of background and experience to contribute to the highly interdisciplinary research programme. We strongly value and
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through the Researcher Academy’s Training Programme, those based within the Faculty of Engineering have access to bespoke courses developed for Engineering PGRs. including sessions on paper writing
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equivalent, in Engineering, Computer Science, Physics or Mathematics with evidence of programming experience. Equality, diversity and inclusion is fundamental to the success of RAINZ CDT and is at the heart
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PhD Studentship: Multi-robot Cyber-physical Systems for Solar Farm Health Monitoring and Maintenance
of operation and power requirements. Applicants should have a First or strong Upper Second-class honours degree (2:1 with 65% average), or international equivalent, in Engineering, Computer Science, Physics