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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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Department: School of Computer Science Details of Studentship: Fully Funded PhD Studentships Applications are invited from Home and International students for a number of fully-funded PhD
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by developing AI methods that improve recognition of rare species while providing reliable measures of uncertainty. Using state-of-the-art computer vision approaches — vision transformers, self
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learning and experience in two or more of: computer vision, sensors/sensor fusion, robotics fundamentals. • Proficient in programming languages such as Python and C++; experience with frameworks such as
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will be expected to contribute to teaching at the Institute of Health Informatics, with the commitment being equivalent to six months teaching over the lifetime of the PhD. About the role The student
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, visions and concerns in innovation. Entry requirements The standard minimum entry requirement is 2:1 in Geography, Sociology, Political Science, Anthropology, Design, Architecture, Engineering, Computer
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PhD programme focused solely on the safety of artificial intelligence (AI). Our vision is to train future leaders with the research expertise and skills to ensure that the benefits of AI systems
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of short-axis MR image sequences. Training You will be based at the Vision Computing Lab within the School of Computing Sciences, which specializes in deep learning for medical image analysis and neural
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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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the UKRI Home Fees for a Masters’ and/or PhD programme, and an annual tax-free stipend (valued at £22,780 in October 2025). As part of your award, you will be able to access additional funding to help cover