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Rolls-Royce, this project will use both experimental and computational aspects to explore the aerodynamic design space for coupled intake/fan configurations that are required to deliver more efficient
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numberSATM533 Entry requirements Applicants must have a B.Sc. in electronic / information engineering or computer science and must either have or close to having a Master’s degree (must be completed by the time
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learning from in-service vehicle fleets and predicting remaining useful life. Applications of artificial intelligence and computer science to battery state estimation. Reduced-authority control of hybrid
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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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, in collaboration with Rolls-Royce, will develop innovative coatings to safely contain hydrogen in critical aerospace materials through experimental and computational modelling work. You’ll join a
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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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with engineering, physics, mathematics, acoustics, fluids, electronics or instrumentation background. Prior experience in computational modelling is beneficial, but not mandatory. Similarly, experience
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evaluation. Prognostics is an essential part of condition-based maintenance (CBM), described as predicting the remaining useful life (RUL) of a system. It is also a key technology for an integrated vehicle
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the identification of topologies and technologies that can support current and future geared architectures. Within this context applying Model Based Systems Engineering principles for defining requirements and
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, computational modelling and experimental work. You’ll join a pioneering multidisciplinary team that values equity, diversity, and inclusion, gaining unique expertise in turbomachinery pump development, hydrogen