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Field
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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
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or experience in digital image processing, computer vision, machine learning, data science, or a related field. Familiarity with Python libraries such as NumPy, OpenCV, Matplotlib, or similar scientific computing
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, Machine Learning, Data Science, Computer Science, Electrical Engineering, Biomedical Engineering, or a related field. Experience with image analysis, computer programming using Python and R, and machine
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-VIS-NIR). Experience in hyperspectral data processing (HMSPL, μXRF, μXAS) and statistical analysis (clustering, machine learning) is preferred. Familiarity with fossilization processes and taphonomic
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individuals participating in studies investigating the cardiovascular consequences of preterm birth. By combining fluid dynamics, machine learning, and advanced imaging analysis, the project seeks to develop
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 18 hours ago
of microscopy, multiplexed immunofluorescence, spatial/protein imaging, or image-derived single-cell phenotypes. Machine learning, latent variable modeling, variational autoencoders, optimal transport, graph
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multiple modalities of medical imaging (e.g. fundoscopy images, OCT scans, MRI, CT, X-ray and digital pathology). We bridge the gap between machine learning research and clinical practice through fruitful
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Engineering, or related field. At least 3 years of relevant experience in computer vision, artificial intelligence, etc. Proficiency in programming languages such as C and Python Proficiency in deep learning
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Paravision Micro-CT, optical imaging, photoacoustic imaging, PET, or SPECT Artificial intelligence or machine learning for biomedical image analysis Python, MATLAB, C++, or similar scientific programming
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machine learning and AI algorithms and software that combine omics and imaging data to discover novel biological information and biomarkers. The incumbent reports to the Clinical Research Manager for