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; distributionally robust optimization; 2) Graph Neural Networks, Large Language Models (LLMs), and geometric deep learning; and 3) federated learning and privacy preserving computing. Basic Qualifications Candidates
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imaging strategies, including reinforcement-learning approaches that dynamically optimize sampling based on environmental conditions such as turbidity and currents Lead the preparation of manuscripts
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a view to identifying optimal regulatory strategies for reducing the deleterious effects of ID, the project pursues five main sub-objectives: (1) to map the non-legal structural factors causing ID
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design and execute experiments using lung cancer and lung infection Organ Chips. Develop, optimize, and characterize human lung microphysiological models for translational studies. Analyze and interpret
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reporting procedures for any incident or event that did affect or potentially could affect the project goals and workflow. Optimize protocols and improve methods currently employed. Coordinates work
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
learning, and create personal and professional sustainability. We optimize our partnership with the UNC Health System through close collaboration and commitment to service. OUR VISION Our vision is to be