35 parallel-programming "Intelligent Systems Group" PhD positions at Cranfield University
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, Artificial Intelligence, Data Science, or other relevant STEM disciplines. Experience in one of more of offshore systems, sustainability assessment, programming, data analysis or AI modelling would be
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This PhD project will focus on developing, evaluating, and demonstrating an intelligent solution of diagnosis and prognosis for rotating machinery to enhance safety, reliability, maintainability and
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disciplines. Experience in one or more of offshore systems, advanced sensors, experiments, programming, data analysis or AI modelling would be advantageous but is not essential. Applicants should have strong
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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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, and intelligent systems. This work aligns with global priorities in energy decarbonisation, materials innovation, and green transport, making it both timely and strategically important. The primary
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Are you interested in shaping the future of zero-emission transport systems? This PhD study, fully funded by the Faraday Institution, facilitates the use of next-generation Lithium-Sulfur (Li-S
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solutions into real-world engineering systems. These skills would make the student a future leader in the aerospace sector and broader intelligent systems industries, positioning the graduate strongly for
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-based additive manufacturing, arc and laser directed energy deposition, thermal–mechanical modelling, and intelligent process monitoring and control for fusion energy applications. We welcome
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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
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arc energy distribution becomes particularly complex in scenarios like parallel-pass deposition, thin-wall deposition, and off-centre or out-of-position deposition. Additionally, FEA models are focused