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University of California, San Francisco | San Francisco, California | United States | about 13 hours ago
/compensation-and-benefits/index.html Department Description The UCSF Department of Radiology Imaging IT team architects, implements, and manages the computer systems and networks needed to support more
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integration and AI models tailored for fish behaviour, health, and stress signal analysis. Investigate and apply novel machine learning and deep learning techniques for pattern recognition, classification, and
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of practice parameters, imaging techniques, cross-sectional anatomy, principles of electromagnetic and computer sciences, patient care/positioning, and MR safety requirements. Skills / Knowledge / Abilities MRI
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multi-modal image registration, based on state-of-the-art machine learning approaches. The developed methods will be applied for ultrasound-based navigation in a novel ultrasound engine designed to drive
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testing of machine learning/AI algorithms Integration of radiomic and biological datasets Working closely with Medical Physics colleagues on reviewing recommendations for detection of specific metabolites
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solid understanding of data science approaches including deep learning prediction and classification models. What we can offer you This role offers excellent training in computer vision and machine
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; intermittently standing or walking with objects weighing up to 25 pounds; and sitting at a computer workstation for extended periods of time; and occasionally working at heights above four feet and/or in confined
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data dictionaries for discrete data. Write, Implement, and develop efficient code and machine learning tools and pipelines for data processing and analysis. Work with collaborators to implement emerging
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University of California, San Francisco | San Francisco, California | United States | about 13 hours ago
, interpersonal, verbal, and written communication skills. Knowledge of computer operation, keyboard functions, calculator, copier and fax machine operation to including MS Office. Proactive and assertive account
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texts. By using a mixed method approach, we propose to make the erased texts readable again, and then edit, translate and study them. Combining multispectral image capture and analysis with machine