86 software-verification-computer-science-"insights"-"Washington-University-in-St" positions at Cranfield University
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multilayer printed circuit boards (PCBs). It draws from disciplines including electrical and electronic engineering, embedded systems, computer vision, and cybersecurity. The ability to verify hardware without
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actionable insights through AI-powered data analysis. This multidisciplinary field combines software engineering, artificial intelligence, and human-computer interaction to create solutions that are both
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advance academic understanding of coordination processes in international technology development while providing practical insights for similar initiatives, enhancing knowledge of how transformative
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Smart sanitation technology represents a critical intersection of automation engineering, embedded systems, and global health innovation. With 3.6 billion people worldwide lacking access to safely
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Organisation Cranfield University Faculty or Department Faculty of Engineering and Applied Sciences Based at Cranfield Campus, Cranfield, Bedfordshire Hours of work 37 hours per week, normally
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Design and Manufacturing Engineering to Tackle Global Sanitation Challenges - MSc by Research or PhD
, aerospace, automotive, medical device, or consumer product industries. Graduates will possess strong technical capabilities in design software, hands-on manufacturing experience, project management skills
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honours degree in materials science, physics, engineering, or a related discipline. The ideal candidate will be self-motivated, with an interest in both computational modelling and practical manufacturing
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analytical techniques and microbiology methods, and direct contribution to technology development through analytical insights. Students will gain exposure to both cutting-edge analytical research and practical
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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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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
complex engineering data and deliver insights that are robust, adaptable, and applicable across complex, high-value, safety-critical domains. This research will contribute to shaping the next generation of