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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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This PhD opportunity at Cranfield University invites ambitious candidates to explore the frontier of energy-efficient intelligent systems by embedding AI into low-power, long-life hardware platforms
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Due to unique properties of supercritical CO2 (sCO2), power generation systems using sCO2 as working fluid have many advantages over their counterparts, such as gas turbines and steam turbine power
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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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uncertainty and dynamic conditions. In complex electronic systems, ensuring reliability and minimizing downtime are critical challenges. AI-driven fault diagnosis and self-healing electronics offer innovative
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This PhD opportunity at Cranfield University invites candidates to explore the integration of AI into certification and lifecycle monitoring processes for safety-critical systems. The project delves
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This PhD opportunity at Cranfield University invites candidates to pioneer research in embedding AI into electronic hardware to enhance security and trustworthiness in safety-critical systems
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categories for a better capability of managing the uncertainty related to system complexity and data availability to achieve more accurate RUL estimations The student will have the opportunity to work with
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knowledge co-evolution and addressing complex challenges in a super-intelligent society. This project is situated within the rapidly evolving field of Cyber-Physical-Social Systems (CPSS), which is of
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research projects across areas such as: Zero Emission Technologies. Ultra Efficient Aircraft, Propulsion, Aerodynamics, Structures and Systems. Aerospace Materials, Manufacturing, and Life Cycle Analysis