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research and strong written and oral communication skills, as we can complete existing strengths with targeted training. Funding This fully funded Connected Waters Leverhulme Doctoral programme studentship
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to industrial clients such as Boeing, BAE Systems, Rolls-Royce, Meggitt, Thales, MOD, Bombardier, QinetiQ, Thales, Network Rail, Schlumberger and Alstom. Entry requirements A minimum of a 2:1 first degree in a
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research and strong written and oral communication skills, as we can complete existing strengths with targeted training. Funding Sponsored by the Leverhulme Trust and Cranfield University, this Connected
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to ensuring safe, reliable, and high-performance communications. The development of 6G based AI networks with integrated TN and NTN infrastructures provides new opportunities for UAV tracking
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to the development of digital twin technologies for sCO2 power generation systems. The Centre for Propulsion and Thermal Power Engineering has a key focus and a proven track record on gas turbine performance, gas path
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targets the development of advanced coatings to prevent cell-to-cell propagation during runaway events. It combines experimental studies, numerical modelling, and real-world burner rig testing, culminating
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supporting the Net Zero 2050 target. This PhD project will develop an AI-enabled framework that optimizes wind turbine control and predictive maintenance. Using Deep Reinforcement Learning (DRL), the system
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rated as ‘world-leading’ or ‘internationally excellent’. This PhD will be based within the Centre for Space Systems and the Resilient PNT research group, both of which have strong track records in
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This self-funded PhD research project aims to advance the emerging research topics on physics-informed machine learning techniques with the targeted application on predictive maintenance (PdM
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. The project focuses on power-aware computing, thermal optimization, and sustainable electronic design, targeting critical applications in aerospace, healthcare, and industrial automation. Hosted by the renowned