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automation integration and deployment of image segmentation algorithms for the automated assessment of thin-film solar cell fabrication processes (e.g. layer quality, defects, morphology) within NOMAD Oasis
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motivated Preferred Qualifications: Experience with serial section EM Histology Viral and immuno labeling Stereotaxic surgery Image analysis software and systems (e.g. FIJI/ImageJ, EyeWire) Light microscopy
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appropriate Reason Codes. Perform corrections and posting to payment transactions that have been edited during the electronic ERA posting process or transactions that could not be posted due to missing or bad
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Veterinärmedizinische Universität Wien (University of Veterinary Medicine Vienna) | Austria | about 6 hours ago
German level (C1) • Experience and skills in the application of modern imaging technologies (e.g. µCT methods) in the representation of biological processes in infection medicine) Main Research Field
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School graduates over a thousand students who are ready to take on great ambitions and challenges. For more details, please view: https://www.ntu.edu.sg/eee This position is part of the research project
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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
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investigate deep learning architectures capable of learning microstructure-property mappings, including convolutional neural networks for microstructure image analysis, graph-based representations
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: Full-time academic position with UF Radiology and Imaging. Provide high quality service in a friendly academic setting, high functioning under pressure. Serve as a mentor to train a great group of
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Eligibility criteria - physics with knowledge in optics - knowledge in microscopy - knowledge in single-molecule imaging (acquisition and processing) - knowledge in photophysics - knowledge in cell culture
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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