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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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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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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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of practice parameters, imaging techniques, cross-sectional anatomy, principles of electromagnetic and computer sciences, patient care/positioning, and MR safety requirements. Skills / Knowledge / Abilities MRI
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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
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Neuroengineering alongside the Comprehensive Neuroscience Center. UAB has recently inaugurated a University-wide Consortium for Neuroengineering and Brain-Computer Interfaces Create a Job Match for Similar Jobs
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) at the University of Florida (UF) is seeking a highly motivated and ambitious Postdoctoral Researcher with a strong background in Artificial Intelligence and Machine Learning (AI/ML). This is an exciting opportunity
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motivated Neuroscience postdoctoral fellow. In addition to neuroscience research experience, having familiar with machine learning/AI/ big data processing will be an asset. A major part of this PDF