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practical solutions for safer participation. Projects may be supervised or co-supervised by experts from Engineering Science and the Medical Sciences Division. Potential Supervisors: Prof. Thomas Okell, Prof
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proposal. This PhD will evaluate the efficacy and suitability of digital image collection and analysis for beach litter characterisation on heavily-littered coastlines, in partnership with community groups
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of computer vision and machine learning Proficiency in English (oral and written) Experience with Deep Learning is a plus To Apply: Please send a long CV, motivation letter, and academic transcripts to Prof
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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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results from human decision-making to inform the design of this new paradigm, and feed the results of the latter back into human decision-making to help make it more explainable. The PhD student will: (1
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: environmental monitoring, AI, computer vision or multispectral imaging. Entry Requirements At least UK equivalence Bachelors (Honours) 2:1. English Language requirement (Faculty of Science equivalent: IELTS 6.5
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the position. The vacant position is part of a collaboration between the Colour Vision and Retinal Imaging Laboratory headed by Prof. Rigmor C. Baraas, the Molecular Ecology Group headed by Jørn Henrik Sønstebø
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, and essential. It enables powerful applications in gas sensing, spectroscopy, noninvasive biomedical imaging, thermal vision, and energy harvesting. From autonomous vehicles to medical diagnostics and
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to the human eye, infrared light is everywhere, and essential. It enables powerful applications in gas sensing, spectroscopy, noninvasive biomedical imaging, thermal vision, and energy harvesting. From
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related disciplines Quantitative imaging, data analysis, or computer vision Numerical modeling of biological systems or continuum mechanics Machine learning/AI, particularly explainable AI (XAI) Hands