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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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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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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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computer workstation for extended periods of time; and occasionally working at heights above four feet and/or in confined spaces. Also involves regular to occasional risk of injury from moving, lifting
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/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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standardized situations. Ability to utilize or learn basic computer functions. CERTIFICATES, LICENSES AND REGISTRATIONS Attend Serv-Safe/HACCP course within one year of employment from classification date
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Desired Qualifications* PACS experience as well as proficient computer entry skills. Experience with digital imaging in an inpatient and trauma setting. Familiar with GE C-arms, Medtronic O-arm, Shimadzu
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 6 days ago
machine learning to identify likely Jim Crow laws. The next phase of the project will expand this work to include the state of Texas and will endeavor to identify both Jim Crow and Juan Crow laws
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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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utilizes a widely available diffraction-limited spinning disc confocal microscope (although not limited to this modality) for imaging. A single-step, machine-learning based approach is then applied