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professional network spanning academia, industry, and national research centres. Through this multidisciplinary project, the student will develop expertise in: Contribute to the development and operation of
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operational efficiency, and provide valuable data insights for improved system operation. Cranfield’s world-class expertise, large-scale facilities and unrivalled industry partnerships is creating leaders in
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operation of autonomous systems in complex, real-world conditions. This PhD project aims to develop resilient Position, Navigation and Timing (PNT) systems for autonomous transport, addressing a critical
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the development of specialized hardware architectures capable of efficient, real-time processing. Embedded AI hardware architectures, including neuromorphic processors and low-power AI accelerators
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costs. Condition monitoring (CM) of rolling element bearings, hereafter called bearings, has been the main point of attention for many decades in the industry for maintenance. This is because bearings
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to develop the coagulation process for phosphorus removal from wastewater. This is an experimental program that will explore how the type of phosphorus species and water characteristics influence
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skills and desirably some computer modelling experience, and an ability to work in a multidisciplinary team and engage confidently with partners. You will have a track record of publishing high impact
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of researchers who are all working on various analytical and experimental projects within the Centre for Assured and Connected Autonomy. The research will significantly enhance aircraft maintenance processes by
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enhancing electronic performance and resilience using AI techniques. The research aims to develop intelligent, adaptive, and high-performance electronic architectures that support real-time processing, energy
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thermodynamically. Performance design optimization and advanced performance simulation methods will be investigated, and corresponding computer software will be developed. The research will contribute