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emergency medicine, computer vision, or data science are highly encouraged to apply. The ideal candidate is self-directed, detail-oriented, and an effective communicator in both written and spoken English
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and expanding team. You’ll play a key role in our success through your code, publications, and strategic promotion of our work. * PhD in Computer Science, Biomedical Informatics, Machine Learning
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hands-on experience in areas such as computer vision, deep learning, multi-modal sensing, robotics, structural health monitoring, or digital twin technologies. (Fresh PhD graduates are welcome
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 1 day ago
machine-learning methods to investigate the deep-time controls on copper mineralisation. The role will involve developing reproducible computational workflows, generating predictive maps of copper
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Science and the Cognition and Perception Program of the Department of Psychology at New York University have a one-year postdoc position available, supported by our Visual Neuroscience Training Program. It
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given that the candidate has formal competence in machine learning and/or image analysis/computer vision Foreign completed degrees (M.Sc.-level) must corresponding to a minimum of four years in
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samples. Apply machine learning and deep learning techniques to automate segmentation and quantitative analysis of tomographic refractive-index data from cells and tissue samples. Apply the developed
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applicant will have a PhD in vision science, computer science, or a related field. Experience in cloud-based and mobile image processing for rapid object and face recognition and in use of head-mounted eye
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healthcare data. * A team player who thrives as a member of a highly functional cross-disciplinary team Preferred Elements * B.S, M.S., and/or PhD in Computer Science, Biomedical Informatics, Machine Learning
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-accelerated computation for large-scale 3D reconstruction. Experience applying machine learning or deep learning to microscopy or tomographic imaging, including segmentation and quantitative analysis. Hands