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on healthcare data. - Experience in Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL) particularly in Natural Language Processing (NLP) and Computer Vision (CV) - strong record
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. in Computer Science, Electrical Engineering, Biomedical Engineering, or a related field, with expertise in computer vision or medical image analysis. 2. Demonstrated research experience in 2D/3D
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National Aeronautics and Space Administration (NASA) | Hampton, Virginia | United States | 20 days ago
the computational work. Researchers in the group have experience with crystal plasticity using finite element and fast Fourier transform methods, fatigue indicator parameters, process modeling and machine learning
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AgriLife is uniquely positioned to improve lives, environments and the Texas economy through education, research, extension and service. Click here to learn more about how you can be a part of AgriLife and
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 8 hours ago
, contributors to our research outputs and an important reason why Carolina is one of the leading public research institutions in the country. UNC-Chapel Hill offers postdocs comprehensive medical and vision
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, integrates, and evaluates innovative solutions in autonomous systems, including artificial intelligence (AI), machine learning, robotics, control systems, sensing technologies, and related disciplines
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towards a shared goal. You will be responsible for the design and pilot testing of machine learning-based automated ultrasound video analysis models that incorporate temporal reasoning. The research will
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 2 months ago
computer vision and/or audio(-visual) machine learning (e.g., multi-object tracking, speaker/source localisation, multimodal fusion). Experience with deep learning frameworks (PyTorch or equivalent) and
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slide imaging analysis in computational pathology is essential. Applicants should have a solid publication record and demonstrated experience in computer vision or analysis of pathology images
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than 18,500 people, including over 14,000 students and 4,000 researchers from more than 120 different countries. Postdoc in ML-Based Co-Design at EPFL Mission The EPFL computer vision lab (https://www.epfl.ch