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. The integration of AI into hardware not only enhances performance but also reduces energy consumption, addressing the growing demand for sustainable and efficient computing solutions. This PhD project delves
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project would suit students with a background in electronics, embedded programming, signal processing, vibration measurement and analysis, maintenance engineering, and electro-mechanical engineering
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electronics, embedded programming, signal processing, vibration measurement and analysis, maintenance engineering, and electro-mechanical engineering. Funding This is a self-funded PhD. Find out more about fees
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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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Organisation Cranfield University Faculty or Department Faculty of Engineering and Applied Sciences Based at Cranfield Campus, Cranfield, Bedfordshire Hours of work 37 hours per week, normally
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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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disruptive aircraft configurations involves combining advanced engineering practices, including computing power, sensing, AI/ML, and system-level engineering. Comprehensive verification and validation
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the £65 million Digital Aviation Research and Technology Centre (DARTeC), leading advancements in aircraft electrification, autonomous systems, and secure intelligent hardware. Through collaborations
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for knowledge exchange activities with a particular focus on Knowledge Transfer Partnerships (KTPS; long established UK-wide programme ). The postholder will be responsible for supporting the post-award
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the safe adoption of hydrogen in aerospace materials through advanced experimental and computational modelling. You'll join a diverse, multidisciplinary team committed to equity, diversity, and inclusion