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—remains a critical challenge. This project will focus on designing AI-driven cognitive navigation solutions that can adaptively fuse multiple sensor sources under uncertainty, enabling safe and efficient
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Francesco Fanicchia is a recognised expert in advanced surface engineering and the development of multifunctional protective coatings, specialising in thermal barriers and fire-resistant materials. As a
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DEPARTMENT OF HEALTH TECHNOLOGY AND INFORMATICS Research Assistant Professor in Medical Laboratory Science / Biomedical Science / Medical Imaging and Radiation Science / Medical Physics / Medical
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Research Groups at the Faculty of Engineering, which conduct cutting-edge research into electric propulsion systems, composite materials, and advanced simulation technologies. Vision We are seeking a highly
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This exciting opportunity is based within the Power Electronics, Machines and Control (PEMC) and Composites Research Groups at the Faculty of Engineering, which conduct cutting-edge research
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Department/Location: Department of Engineering, Central Cambridge A position exists, for a Research Assistant/Associate in the Department of Engineering, to work on experimental investigations
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in partnership to achieve excellence in public and global health research, education and translation of knowledge into policy and practice. This is an 18 month Research Assistant position, with
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to produce cutting-edge research. Prospective applicants must: Hold a good honours degree in an appropriate subject (including Computer Science, Physics, Maths, Engineering) Knowledge of modern machine
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year. Working at the intersection of water engineering, environmental microbiology, robotics, and lifecycle analysis, you will evaluate autonomous underwater skimming robots that minimise energy use in
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
relationships, together with deep domain expertise. These methods open new possibilities for extracting and connecting knowledge at scale. The goal is to enhance digital twins with the capability to interpret