44 operations-management-associate-professor PhD positions at Cranfield University in Uk
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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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(conductivity, heat capacity, flame resistance). Advanced finite element modelling will then correlate microstructural features to heat-transfer performance. The candidate will design and build a burner-rig test
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investigate strategies to enhance communication security, focusing on resilience against jamming and spoofing attacks. Students will work on designing secure architectures that ensure data integrity and system
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This PhD opportunity at Cranfield University explores how next-generation AI models can be embedded within resource-constrained electronic systems to enable intelligent, real-time performance
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-based solutions (NbS) for water and wastewater treatment. The research will explore sustainable engineering strategies to boost their performance to deliver benefits for the environment and society. The
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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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significantly reduce the amount of vibration data to be stored on edge devices or sent to the clouds. Hence, this project's results will have a high impact on reducing the hardware installation and operation
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at the internationally recognised IVHM Centre, the research is supported by collaborations with Boeing, Rolls-Royce, Thales, and UKRI, offering a unique environment for cutting-edge work in fault-tolerant hardware
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
amounts of maintenance and operational data, from sensor streams to technical logs, yet much of it remains unstructured, fragmented, and underused. Hidden within these records are insights that could help
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for reconstructing full 3D temperature fields from partial temperature measurements, utilising monitoring techniques deployable in industrial settings. This work will provide critical thermal insights for diagnosing