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related discipline. This project would suit a candidate with a background in mechanical, control or aerospace engineering, physics, mathematics, or other relevant engineering/science degree. The ideal
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, environmental science, urban sustainability, geospatial analysis, or quantitative modelling. We particularly welcome applicants who are excited about integrating ecological understanding with data-driven methods
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, robotics, microbiology, environmental science, chemistry, physics or data science. Applications would be keen to blend hands‑on experimentation with advanced analytics to create low‑carbon, nature‑based
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engagement with industry, data-driven environmental decision-making and applied modelling experience directly relevant to careers in academia, consultancy, regulatory science, conservation NGOs and
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influence perceptions. It will subsequently explore and evaluate the types of information and knowledge required to improve the understanding and appreciation of urban blue spaces, before investigating
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and kinematic models with machine-learning-based channel state information (CSI) prediction to enable robust, low-latency connectivity across multi-layer NTN systems. This PhD project sits
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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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function of urban blue spaces influence perceptions. It will subsequently explore and evaluate the types of information and knowledge required to improve the understanding and appreciation of urban blue
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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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; gender diversity in Science, Technology, Engineering and Mathematics (STEM) through our Athena SWAN Bronze award and action plan, we are members of the Women’s Engineering Society (WES) and Working