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Operating Systems, Hardware, and Storage. This role contributes to the development of new solutions, enhancement of existing systems, and resolution of complex technical systems. Key Responsibilities
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. MINIMUM QUALIFICATIONS Bachelor?s degree and three to four years of relevant experience, or equivalent combination of education and experience. Demonstrated organizational skills within large/complex
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management to include fiscal management, correspondence, personnel matters, and complex level decisions exercising initiative and independent judgment. Supervision of Administrative Assistant II and other
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development of network systems. Analyzes, evaluates, and makes recommendations regarding new technology and trends to meet corporate needs. Provides troubleshooting services on complex network problems
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University of Texas Health Science Center San Antonio | San Antonio, Texas | United States | 1 day ago
of EMS systems. Direct-field experience with local, state and federal EMS programs. Progressively graded medical control responsibilities for complex EMS systems with acquired proficiencies in fire-based
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patient care mission. The Wexner Medical Centers seven hospitals and its network of community-based offices and care centers manage more than 3.2 million outpatient visits each year. In 2024, the Ohio State
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process Applications will be reviewed on a rolling basis until the position is filled. Additional comments Project Overview Cells sense, integrate, and respond to dynamic stimuli through complex signaling
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complex decisions independently, and committed to advancing health equity through community-based engagement and education. Key Responsibilities Coordinate, develop, implement, and train internal and
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University of California, San Francisco | San Francisco, California | United States | about 11 hours ago
classification at UCSF. To learn more about the benefits of working at UCSF, including total compensation, please visit: https://ucnet.universityofcalifornia.edu/compensation-and-benefits/index.html Department
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their applications. Using machine learning and related tools to enhance quantum memory advantages in stochastic simulation. Using advanced tensor network techniques to enhance the modelling of complex, memoryful open