34 postdoc-distributed-algorithms positions at University of Virginia in United States
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) + applicable shift differential pay Multiple Shifts Available Entry level/novice performs and participates in decontamination, cleaning, assembling, packaging, scanning, sterilization, storage and distribution
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learning algorithms on graphs to model, characterize, predict, and design the thermal and physical behaviors of diverse material systems. Responsibilities also include the development of software codes
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science of science, network science, and natural language processing. As part of a small research team, the postdoc will help lead efforts to provide a quantitative model of global competitiveness
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submission to journals and conferences. Present research findings at seminars, conferences, and scientific venues. Develop innovative and robust machine learning algorithms to personalize interventions
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Provides safe transport of the right patient to the right location while maintaining a high level of productivity.Responsible for patient transports distributing equipment and supplies morgue
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prevalence data collection, evidence-based policies, procedures, and protocols, and advisement of appropriate support surfaces, products, and staff decision-making algorithms. • Provides consultation and
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to ensure the best care possible is being given. Provides clinical pharmaceutical care to patients. Enhances the quality of delivery of care. Demonstrates proficiency in Pharmacy distributive services
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sufficient attention and follow through. Takes, documents, and distributes minutes as necessary. Assists the Assistant Director with creating instructional documents for promotion and tenure (P&T) to aid
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work requirements and assignments, ensuring efficient use and distribution of scheduled workload. Directs daily the patient and equipment transport workflows, providing problem resolution and
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Duties Include: Composing and distributing memos to students, faculty, and others as it relates to faculty’s courses and other obligations. Work with undergraduate students to solve scheduling problems and