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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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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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Deadline: 7th January 2026 One fully funded, full-time PhD position to work with Dr. Viacheslav Borovitskiy in his new research group at the School of Informatics, University of Edinburgh. Our
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. self-supervised learning techniques, particularly suited to infrastructure applications where labelled data is scarce, enabling models to learn from the data itself without relying on extensive human
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quality, diversity, and biological relevance using standard metrics and expert review. Anonymised digital images from tissues in biobanks will be used to train generative models on university computing
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(optional). Person specification: Prior experience in computer coding (e.g., Python, SLiM), AI modelling, and understanding of evolutionary or conservation genetics / genomics is desirable. Good teamwork
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). Design and fabricate patterned surfaces optimised for enzyme immobilisation. Assess synergistic antibiofilm efficacy under static and dynamic (flow-based) biofilm models. Apply advanced microscopy, protein
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<programme title> on the Programme Choice page. You will be prompted to enter details of the studentship in the Funding and Research Details sections of the form. Candidate requirements: Applicants must hold
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performance of AI models for fall detection. The research will combine experimental studies on different floor systems, finite element simulations of vibration propagation, and AI-based signal analysis
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synergistically, similar to how systems work in nature. Experimental work will include the following indicative activities: Designing and developing CAD models of test coupons and other structures Fabrication