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of complex, dynamic flows relevant to closely coupled engine aircraft configurations. You’ll join a pioneering multidisciplinary team that values equity, diversity, and inclusion, gaining unique expertise in
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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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recycling and resource recovery. Cranfield University stands out as an ideal institution for this research due to its extensive resources and expertise in engineering and digital technologies
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, large-scale facilities and unrivalled industry partnerships are creating leaders in technology and management globally. Learn more about Cranfield and our unique impact here . The Research and Innovation
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from such machines to derive algorithms expressing their state of health and next maintenance needs. A background in both engineering and machine learning would be useful, although help is readily
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science and engineering? We are recruiting a motivated PhD candidate to undertake an exciting project within the EPSRC Energy Transfer Technologies Doctoral Training Hub. As a student of the Hub, you will
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Technology Centre (DARTeC), leading advancements in aircraft electrification, autonomous systems, and secure intelligent hardware. Through collaborations with the Aerospace Integration Research Centre (AIRC
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technology and management globally. Learn more about Cranfield and our unique impact here . The University is supported by a wide range of professional services. The Research and Innovation Office (RIO
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there be interest, there is also the possibility of developing teaching and supervision skills on our MSc Astronautics and Space Engineering programme. Sponsored by EPSRC and Cranfield University, this DLA