76 postdoctoral-image-processing-in-computer-science-"EPIC" positions at Cranfield University
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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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Families, and sponsors of International Women in Engineering Day. We are also Disability Confident Level 1 Employers and members of the Business Disability Forum and Stonewall University Champions Programme
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Develop practical, industry-transforming technology in this hands-on PhD program focused on immediate industrial applications. This exclusive opportunity places you directly at the interface between
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solutions. You will study the collaboration and coordination processes that enable successful technology development across international partnerships. This research combines hands-on engagement with advanced
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, and evidence-based recommendations for optimizing waste treatment processes. Results will include published research in high-impact environmental and analytical chemistry journals, standardized testing
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
intelligence, particularly in computer vision and deep learning, offer an opportunity to automate and enhance damage assessment by learning patterns from multimodal data. This research seeks to bridge the gap
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conduct interdisciplinary research combining software engineering, artificial intelligence, IoT development, and human-computer interaction to create intelligent software systems that serve both technical
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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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Design and Manufacturing Engineering to Tackle Global Sanitation Challenges - MSc by Research or PhD
methodologies for sanitation technology, optimized manufacturing processes for cost-effective production, and comprehensive documentation for scalable manufacturing implementation. Results will include published
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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