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About Us The applicant will join the new Wellcome-funded Imaging Machine learning And Genetics in Neurodevelopment (IMAGINE) lab, in the Research Department of Biomedical Computing. The post will
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assess how effectively imaging techniques capture or enhance the taxonomic resolution of traditional net sampling. Training You will gain skills in plankton taxonomy, image processing, ecological
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new Wellcome-funded Imaging Machine learning And Genetics in Neurodevelopment (IMAGINE) lab, in the Research Department of Biomedical Computing. The post will benefit from the extensive and broad
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biological materials. The development of novel computer-vision-based techniques for contactless detection, quantification, and prevention of sport injury. The development of robotic humanoid simulator and
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in AI. Previous publication record in relevant fields: AI, machine learning, computer vision, etc. Previous successful project on a relevant topic. Good knowledge of statistics, probability
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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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contribute significantly to these growing fields. This PhD position is ideal for candidates interested in the following areas of machine learning: Geometric learning: exploiting the structure of data (e.g
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for Real-World Optimisation and AI Applications Brain-Computer Interfaces & their Applications Computational Neuroscience: Reinforcement Learning and Microzones in the Cerebellum Explainable Generative
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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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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