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Field
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learning; experience with 3D data or point cloud processing, computer vision, or generative models is a plus. Enjoyment of application-oriented challenges in industrial contexts, translating theory
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project is supervised by Jon Sporring (UCPH) , Anders Bjorholm Dahl (DTU) , Stephen Hall (LU) , and Martin Bech (LU) , combining expertise in mathematical image analysis, computer vision, quantitative
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, School of Information, School of Kinesiology, College of Architecture & Urban Planning, and School of Art & Design to work on robot learning and foundational models, perception and computer vision
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. The project will advanced state of the art AI for NLP or vision or both and embed self-awareness modules within these systems. This will likely involve a combination of the standard methods in these
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. The project will advanced state of the art AI for NLP or vision or both and embed self-awareness modules within these systems. This will likely involve a combination of the standard methods in these
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[Malaysia Campus- VPSSP] An AI-Informed Planetary Health Framework for Equitable AMR Risk Mitigation
ensure local relevance. Required knowledge Artificial Intelligence; Machine Learning; Computer Vision; Bioinformatics; Biomedical Engineering; Neuroscience; Genomics; Medical Physics; Data Science
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. Profile We are looking for a motivated and committed candidate who brings: Mandatory skills Experience with computer vision for motion analysis Master’s degree in Biomechanics, Biomedical Engineering
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Associate in Computer Science for a two-year post within CAPTURE-PH, a multi-centre programme using chest CT and artificial intelligence (AI) to improve the diagnosis, phenotyping and prognostic
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machine/deep learning, computer vision, or applied statistics. Solid programming skills in Python and experience with deep learning frameworks (e.g., PyTorch or TensorFlow) Project funding Other Funding
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doing basic research in areas such as: AI for Science, AI Safety, Bio-inspired Robotics, Biomechanics, Causal Inference, Computational Biology, Computer Graphics, Computer Vision, Control Systems, Deep