589 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" positions at University of Pittsburgh in United States
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issues with data collection. Essential Functions The essential functions for this position include: 1. Day-to-day research operation tasks (e.g., participant screening and recruitment, phone calls
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studies. This includes testing for identity, purity, composition, integrity, safety, activity, stability, viability, and potency assays. Collect background information for testing/experiments/production
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multiple types of specimens. Operates and maintains laboratory equipment and laboratory cleanliness. Keeps detailed and accurate data and logbooks. Organizes/documents results. Maintains inventory, orders
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status. • Collects pertinent information and updates data bases for registry assessments and clinical trial forms. • Escorts subjects/participants to research scanning sites. • Maintains and organizes
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, configuration, monitoring, and lifecycle management. • Assists with the deployment and operation of AI enabled tools, automation platforms, and data driven services that support departmental and enterprise needs
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academic and career goals, select appropriate courses, and plan for degree attainment. Manages small to medium-sized, moderately complex projects. Essential Functions Must be able to use a computer and
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programming and monitoring • Fitness and clinical data collection and entry • Undergraduate research assistants supervision • Oversees research participants and equipment safety standards during exercise
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, and PBMC isolation. Routine data entry into specimen inventory system for the collection, receipt, disbursement, and storage of each sample. Rotation at other PBC labs is required. Pulls samples
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experiences. The EDGE Enrollment Management team is a dynamic, data-driven unit dedicated to growing Pitt's portfolio of workforce-aligned online, master's and professional programs. We integrate creative
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engineering, including, but not limited to, data analytics, simulation, AI/ML, human factors, and operations research applied to address challenges in health systems, manufacturing, materials, robotics, quality