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publications in top-tier venues, and collaborate with colleagues across disciplines. Your research projects will be implemented in collaboration with the Research Center of Intelligent Computing and Data Science
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Applications are invited from PhD studentship candidates with good first degrees in computer science, physics, maths, biology, neuroscience, engineering or other relevant disciplines to join
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develop AI- and deep learning–based computer vision tools to automatically identify and quantify intertidal organisms. Beyond computer vision, it will leverage machine learning for large-scale, data-driven
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, the project accelerates trait data acquisition by applying computer vision to herbarium specimens and field photos, as well as large language models to extract complementary information from literature and
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One fully funded, full-time PhD position to work with Alessandro Suglia in the Embodied, Situated, and Grounded Intelligence (ESGI) group at the School of Informatics, University of Edinburgh
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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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artificial intelligence (AI), it is now possible to generate realistic synthetic images, offering an ethical and scalable way to expand healthy tissue collections and support future research. This project will
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, Urban Studies, Urban Analytics, Environmental Science, Computer Science, Architecture, or an appropriate master’s degree. Familiarity with Python/R programming, GIS and spatial analysis (e.g., ArcGIS
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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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combining high-fidelity computational modelling with artificial intelligence to overcome key barriers in performance. The investigation will focus on optimising core gas exchange and combustion processes