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of artificial intelligence (AI) nowadays, it has become possible to develop a fast-response AI-based condition monitoring system for gas turbine engines. The objective of the project is to develop novel AI-based
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with a background in mechanical, aeronautical, automotive, civil / industrial and/or software engineering (or similar) and/or mathematics and/or physics. The ideal candidate will have a solid background
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Rolls-Royce the project will focus on the development and testing of novel ultrasonic methods to measure intake massflow for aero-engines. This technology has the potential to improve the methods
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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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This is an exciting opportunity for a Self-funded PhD studentship in the Centre for Autonomous and Cyber-Physical Systems associated with the Faculty of Engineering & Applied Sciences at Cranfield
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. Cranfield University is internationally recognised for aerospace and hydrogen technology research, equipped with state-of-the-art hydrogen testing and material analysis facilities. The industry partner
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related discipline. This project would suit the applicants with the background of control engineering, aerospace engineering, mechanical engineering, or electrical engineering. This post will require
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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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, in collaboration with Rolls-Royce, will develop methods for defining fuel systems suitable for the ultra-efficient engines that will enable net zero aviation by 2050. This project aims to deliver a
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propulsion systems. You’ll join the wider CDT multidisciplinary cohort that values equity, diversity, and inclusion, while gaining expertise in aero-engine aerodynamics, analysis of advanced experimental data