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Education: Ph.D. or M.S. in Computer Science, AI, Computer Vision, or related field Experience: 3+ years in computer vision and deep learning, with specific focus on microscopic imaging, generation
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Additive Technologies) team at University of Warwick seeks a creative and motivated research fellow in the area of deep learning for (X-ray) image processing. The appointment is currently until 31 March 2027
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scholarship in “Unsupervised Machine Learning for Cardiovascular Image Analysis”. This opportunity is available to UK (Home) candidates only. Fully-supervised AI techniques have shown remarkable success in
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procedures, including in computational tasks where data visualization, preprocessing, or interpretation can be improved. Devises and deploys custom machine learning approaches where applicable. Provides
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in image processing, quantitative analysis, and biological interpretation Proficiency in AI/machine learning tools for image segmentation, transformation, registration, or tracking Solid mathematical
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Funding for: UK/Home Students We invite applications for a fully funded PhD research scholarship in “Unsupervised Machine Learning for Cardiovascular Image Analysis”. This opportunity is available
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, including in computational tasks where data visualization, preprocessing, or interpretation can be improved. Devises and deploys custom machine learning approaches where applicable. Provides feedback and
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push the boundaries of neural scene representations in a medical imaging context. The successful candidate will work alongside a multidisciplinary team of deep learning researchers, computer vision
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alignment to create system-level composite images. Build and train advanced machine learning models to autonomously detect various PV defects such as hotspots, microcracks. Execute the necessary data
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between complex instances such as point clouds, images or graphs. However, as the modern data are increasingly high-dimensional, OT is also now facing an old problem in optimization and statistical learning