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to train tomorrow’s leaders in earth and environmental science. For further details about the programme please see http://nercgw4plus.ac.uk/ For eligible successful applicants, the studentships comprises
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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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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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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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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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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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(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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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