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Field
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace - In Partnership with Rolls-Royce PhD
system health monitoring, and more efficient maintenance planning. Digital twins offer a powerful foundation but must evolve beyond simulation to truly support engineering decisions. This PhD will develop
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control system that enhances Annual Energy Production (AEP), reduces mechanical stress, and improves fault detection using machine learning (ML) and physics-based modelling. The candidate will gain hands
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, diversity and inclusion and through this appointment process, it is our aim to develop candidate pools that include applicants from all backgrounds and communities. We ask all candidates to submit a copy of
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, Continuum Mechanics, Computer Science, Materials Science, Physics or a related subject, or relevant industrial experience. English language requirements: Applicants must meet the minimum English language
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); The applicants may have a background in any aspect of Materials Science, Metallurgy, Physical science or Engineering. A copy of your undergraduate/Postgraduate degree certificate(s) and transcript (s); Names and
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, combustion, and process optimisation. The project is focussed on the development of novel interface capturing Computational Fluid Dynamics methods for simulating boiling in Nuclear Thermal Hydraulics
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technical expertise in Computational Fluid Dynamics (CFD), simulation methods (including RANS, DNS/ LES), and experimental techniques such as wind tunnel testing and 3D printing. The project will also improve
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or international equivalent in an appropriate subject, including: biomedical sciences, medical physics. Further qualification such as an MRes is advantageous. If your first language is not English, you need
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include simulation and control implementation, data analysis, and knowledge dissemination through technical documentation and stakeholder workshops. This is a full-time, fixed-term role starting 1 September
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architectures and distributed storage integration. Examining the physical arrangement, fire safety, redundancy, and maintenance requirements for embedded storage. Evaluating economic considerations, including