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- VIN UNIVERSITY
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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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(computer vision technologies). The interdisciplinary nature of this PhD will require the integration of environmental science, engineering, and community science methodologies. Supervisors: Primary
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Number of Positions: 1 Eligibility: UK Only Funding: School of Computer Science Scholarship, in support of the EPSRC Grant: Mixed precision in Krylov Methods, providing the award of full academic
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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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This PhD project focuses on advancing computer vision and edge-AI technology for real-time marine monitoring. In collaboration with CEFAS (the Centre for Environment, Fisheries, and Aquaculture
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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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of Warwick. This exciting project, co-supervised by Dr. Sagar Jilka and Dr. Vivek Furtado, focuses on developing a privacy-preserving Artificial Intelligence (AI) tool to predict the worsening of anxiety 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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"intrinsically-aligned" artificial intelligence, where accuracy, fairness and explainability are all taken into account when selecting the "best" AI model. Requirements: The essential selection criteria include