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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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marine ecosystem management in the changing climate. Entry requirements: Applicants will normally need to hold, or expect to gain, at least a 2:1 degree (or equivalent) in Computer Science, Engineering, or
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This is an exciting PhD opportunity to develop innovative AI and computer vision tools to automate the identification and monitoring of UK pollinators from images and videos. Working at
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
intelligence, particularly in computer vision and deep learning, offer an opportunity to automate and enhance damage assessment by learning patterns from multimodal data. This research seeks to bridge the gap
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scanning confocal microscopy and calcium imaging in time-lapse, computational imaging approaches for analysis of images and movie recordings, analysis of the connectome to identify neural circuits
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Geography, Biology, Chemistry, Earth Science or Environmental Science, Computer Science, Engineering, or an appropriate Master’s degree. English language requirements: Applicants must meet the minimum
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collection activities. Supervision will be provided by academics from various disciplines specializing in biomechanics, image processing, and computer vision, alongside orthopaedic surgeons and academics.
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undergraduate degree relevant to each individual project, e.g., Experimental Psychology, Physics, Neuroscience, Computer Science, Electrical Engineering, or a related subject. In addition, an appropriate master’s
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A fully funded 3.5 years PhD position in developing software and computational tools for sustainable supramolecular materials design is available in the group of Assistant Professor Andrew Tarzia
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by exploring a novel therapeutic angle that could overcome the limitations of current anti-inflammatory drugs. How will you do this? You’ll be trained to use state-of-the-art methods like live imaging