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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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following skills: Strong interest in the field of neuroimaging, psychiatry and genetics. Computer skills: Strong level in the main informatics software (FSL, Freesurfer, fMRIprep) and coding languages (R
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 11 hours ago
candidate will be expected to publish in peer-reviewed journals and contribute to the broader NASA Earth Science community's preparation for the next generation of orbital imaging spectrometers. Point
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. Given this, the CUI: Advanced Imaging of Matter Graduate School features an interdisciplinary research and training programme for doctoral students and post-doctoral researchers. It is addressed to young
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information encoding and computation in neocortical circuits. The successful candidate will lead an ambitious project on synaptic and circuit mechanisms of sensory processing in primary visual cortex (V1
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Radiology, Neuroradiology, Interventional Radiology, Nuclear Medicine, Intelligent Imaging Informatics (I3), Research, and Physics. The Body Radiology section focuses primarily on pediatric cancer imaging and
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evaluation. Collaborating with heritage partners (e.g., Swiss National Museum, SIK-ISEA) and preparing evaluation reports and a white paper for applied use. PhD in Digital Humanities, Imaging Science, Computer
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optical imaging (Leung Research Group) The Leung Research Group (https://sites.google.com/view/LeungGroup) in the Department of Intelligent Systems Engineering at the Luddy School of Informatics, Computing
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, engineering, physics, biophysics, applied mathematics, computational biology or a related quantitative field Strong background in deep learning for image analysis / computer vision, ideally on microscopy time
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to explore include mono-chromatic and multi-chromatic illumination, structured illumination, and telecentric illumination distortions. Computer based image analysis approaches will be developed, including