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world. Like the city we call home, UB is distinguished by a culture of resilient optimism, resourceful thinking and pragmatic dreaming that enables us to reach others every day. Visit our website to learn more
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world. Like the city we call home, UB is distinguished by a culture of resilient optimism, resourceful thinking and pragmatic dreaming that enables us to reach others every day. Visit our website to learn more
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optimally interact with a varied population of diverse audiences. We are looking for someone who shares our values and who will support the mission of the university through their work. Qualifications: PhD in
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Systems will participate in the research efforts of developing systems integration, analysis, design, control, and/or optimization models and algorithms for smart energy systems to enable smart and healthy
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the development and testing of new materials. The work will involve reactor design and setup with gas flow capability and process optimization. Qualified candidates should have a Ph.D. in chemistry, physics
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. The candidate is expected to carry out cutting-edge research on the physical layer design and optimization of RHS-enabled or RIS-assisted MIMO communication systems using tools from information theory
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: Investigating membrane fouling mechanisms and mitigation strategies in desalination and water treatment processes. Developing and optimizing functional membranes, including electrically conductive membranes
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
, 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
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the optimization of High- Throughput RNASeq capabilties. The successful candidate will help design and execute next- generation RNASeq experiments with the goal of significantly reducing the cost and increasing
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modeling. 80% research - The project focuses on developing theoretical models using optimization and information theory to improve understanding of plant hydraulic regulation at the leaf, plant, and