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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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Language Model, or Artificial Intelligence be used? The impact of this research will be to enable practitioners and the stakeholders of systems models to make objective assessment of model qualities using
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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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Start Date: Between 1 August 2026 and 1 July 2027 Introduction: This PhD is aligned with an exciting new multi-centre research programme on parallel mesh generation for advancing cutting-edge high
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). The successful candidate will design and prototype intelligent textile/wearable systems capable of sensing, communication, and stimulation. The project will integrate wearable electronics, advanced manufacturing
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strategic priorities in Digital Twins, Environmental Intelligence, and Data-Driven Engineering, using advanced computational modelling to support ecosystem resilience and sustainable management. The project’s
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volumes in a reliable, repeatable, and automated way. This project aims to establish a data-driven, adaptive framework that develops artificial intelligence tools, integrated with advanced geostatistics
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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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. Experience with numerical methods, finite element method, statistics and machine learning is desirable. How to apply: Stage 1: Submit your 2-page curriculum vitae (CV), transcripts and a 300-word statement
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Samuelson and her team on a longitudinal study examining children’s performance on multiple word learning tasks at 18-, 24- and 36-months-of age, as well as their vocabulary growth. There will be