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Field
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. Project Background This project directly supports QCI3's vision of integrated and interconnected implementations by developing essential benchmarking tools that bridge across all three themes of the Hub
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tuition fees. This PhD project in the area of autonomy, navigation and artificial intelligence, aims to advance the development of intelligent and resilient navigation systems for autonomous transport
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of the complex physics governing the interaction between the heat source and the material. Additionally, it seeks to develop an efficient modelling approach to accurately predict and control the temperature field
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growth, development, and reproduction, with a strong emphasis on fundamental discovery and translational potential for crop improvement. What we offer • Co-supervision and collaboration across our three
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of complex metagenomic data. You will also become proficient in lifecycle carbon accounting and data-driven decision-making, all mapped to the Researcher Development Framework at Cranfield University. Regular
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This self-funded PhD research project aims to develop smart sensors based on low-frequency resonance accelerometers for condition monitoring of ultra-speed bearings. The developed smart sensors will
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aims to develop a novel theoretical framework for nonlinear and robust control of dynamical systems from a phase perspective. You will have the opportunity to freely explore multiple research directions
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Applications are invited for one full-time EPSRC Industrial CASE (ICASE) PhD studentship for each project. “Development of natural-ageing-resistant, heat-treatable lean aluminium alloys
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on Artificial Intelligence (AI), Deep Reinforcement Learning (DRL), and Predictive Maintenance for optimizing wind turbine performance and reliability. This research will develop an AI-powered wind turbine
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paid. We expect the stipend to increase each year. Only Home students are eligible for funding. The start date is October 2026. The project aims to develop and optimize metal oxide aerogel materials