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Mission-Inspired priorities of Engineering Net Zero and Artificial Intelligence. This vision also reflects RCA’s institutional research priorities: Climate Crisis and the Circular Economy, and Design & AI
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completion of a 1st Class Master's in Chemistry, Chemical Engineering, or a related field. A background in flow chemistry (and/or high-throughput experimentation), as well as proficiency in programming
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, candidates will be expected to achieve/have achieved a First class honours MEng/MSci or higher degree (or international equivalent) in: Aeronautical/Mechanical Engineering or similar STEM subjects. You need
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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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backgrounds such as in computer science, mathematics (pure or applied), or engineering. The successful applicant will be highly motivated, have excellent time management, and a proven track record in
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will be jointly supervised by: Dr Dominik Leichtle, School of Informatics, University of Edinburgh Dr Elham Kashefi, School of Informatics, University of Edinburgh Dr Theodoros Kapourniotis, National
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of Computing, Engineering and the Built Environment , the largest of the five schools at Edinburgh Napier University. With a practical focus on adding value to the social, cultural, and economic capital of
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candidate with a strong quantitative background (e.g., in computer science, statistics, bioinformatics). The following skills are essential for this project: Excellent programming skills in Python. Proven
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supporting the village of Brigstock, while establishing scientific principles for national flood management strategies. The outcomes will contribute foundational science with tangible community impact by
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, geographically concentrated climate shocks and their interaction with banking and insurance systems. This PhD offers the opportunity to close these critical gaps by integrating cutting-edge flood science with