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learning applied to biomedical images. Position Overview Prof. Tagare is seeking a full-time Postgraduate Research Associate for a 1-year training position focused on computational analysis and machine
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German Cancer Research Center in the Helmholtz Association (DKFZ) | Heidelberg, Baden W rttemberg | Germany | 3 months ago
throughout the Helmholtz Association. Within HI, the Applied Computer Vision Lab (ACVL) at DKFZ develops state-of-the-art methods for image analysis and machine learning, supports researchers in
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of cancer promoting mutations, the checking of which one could model to predict new routes towards preventative cancer. The Research Associate will focus on developing machine-learning (ML) approaches
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Machine learning has recently made significant progress for medical imaging applications including image segmentation, enhancement, and reconstruction. Funded as an Australian Research Council
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filled The overarching aim of this project is to find synergies between methods and ideas of modern machine learning and of statistical mechanics for the study of stochastic dynamics with application
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of California, San Diego investigates how neural circuits control appetite and motivated behavior. A major focus of the laboratory is the development of CaRMA imaging, an experimental framework that links large
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Be You. At Duke, we celebrate individuality and the unique perspectives that each member of our community brings. As the Machine Learning Research Data Analyst, Ophthalmic Imaging, you'll play a
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, demographic, lifestyle, laboratory, imaging and longitudinal health data provides opportunities to apply Artificial Intelligence (AI) and Machine Learning (ML) to colorectal cancer research. Research Aim
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the following will be a plus • Optical instrumentation, single-molecule/ super-resolution microscopy, magnetic/optical tweezers, ultrafast spectroscopy, or other in-situ operando imaging tools • Machine
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Duration: 1-year appointment with possibility of renewal for a 2nd year. About the Department Our research group works at the intersection of machine learning, medical imaging, biomedical engineering, and