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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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collaboration, we are building a high-throughput single-cell analysis platform that combines microfluidics, advanced imaging and AI-based analysis to study gut microbial consortia. You will drive the development
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(this overlaps with the former themes as 2D and 3D vision is often integrated with language). Related papers by the Vision-CAIR members Theme A : Aligning Latent and Image Spaces to Connect
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/biomedical engineering or of relevant scientific field A solid background in machine learning Extensive experience with either computer vision or image analysis Good knowledge of deep learning packages
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The VCC center at KAUST is looking for research scientists in Prof. Wonka's research group. The topics of research are computer vision, computer graphics, and deep learning. A suitable candidate
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Assistant Research Professor (Research Track), Radiology and Imaging Sciences Posting Number req24876 Department Radiology & Imaging Sci Dept Department Website Link https://radiology.medicine.arizona.edu
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attention using psychophysics, TMS, imaging Clay Curtis - action selection and working memory using imaging and eye movements Claude Desplan - color vision in Drosophila using imaging and physiological
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from This Employer https://main.hercjobs.org/jobs/21997486/physician-iii-cardiac-imaging Return to Search Results
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science/biomedical engineering or of relevant scientific field A solid background in machine learning Extensive experience with either computer vision or image analysis Good knowledge of deep learning
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🎯 Research Vision The next generation of software engineering tools will move beyond autocomplete and static code generation toward autonomous, agentic systems — AI developers capable of planning