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This is an exciting PhD opportunity to develop innovative AI and computer vision tools to automate the identification and monitoring of UK pollinators from images and videos. Working at
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equivalent in a related discipline. This project would suit motivated graduates from a wide range of STEM backgrounds—including environmental, civil, chemical or mechanical engineering, computer science
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you with a highly sought-after interdisciplinary skillset bridging ecological theory, modelling, field ecology, agricultural systems and applied environmental science. As a CASE-supported project with
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be interested in applying social science approaches to an environmental setting. However, we welcome applicants from a range of disciplines and experiences, who have a passion for environmental
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This is a self-funded PhD position to work with Dr Adnan Syed in the Surface Engineering and Precision Centre. The PhD project will focus studying high temperature corrosion mechanisms in details
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Women in Engineering Day. We are also Disability Confident Level 1 Employers and members of the Business Disability Forum and Stonewall University Champions Programme. Cranfield Doctoral Network Research
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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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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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This self-funded PhD opportunity explores assured multi-sensor localisation in 6G terrestrial and non-terrestrial networks (TN–NTN), combining GNSS positioning, inertial systems, and vision-based sensors to deliver resilient, high-accuracy positioning. The project sits at the intersection of...
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. The integration of AI into hardware not only enhances performance but also reduces energy consumption, addressing the growing demand for sustainable and efficient computing solutions. This PhD project delves