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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 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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uncertainty quantification into scientific machine learning workflows and optimize the design of computational (ABM) and wet-lab experiments. • Collaborate with mathematical modelers and experimentalists in
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inflow reconstruction techniques for lidar-assisted control and load assessment/validation. Contribute to the development and modelling of wind turbine control methods with the aim to optimize wind turbine
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testing, and advanced process simulation, with the objective of optimizing grinding performance and enhancing resource recovery. The ideal candidate will have a strong background in mineral processing
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, -- mathematical theory for artificial intelligence, -- optimization and numerical computation over manifold, -- systems and control theory, -- algebraic computation theory and cryptography. The position is for two
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resource optimization. o Entanglement dynamics, quantum control protocols, and hybrid quantum-classical algorithms. o Modeling and benchmarking atomic qubit architectures. · Collaboration: Work closely with
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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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and the upgrading of traditional vaccines, breakthrough the key technical bottlenecks in basic research, process development and production of vaccines, continuously optimize the industrial structure
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of linear algebra and numerical optimization Understanding of statistical modeling and inverse problems is desirable Experience with programming languages like Python, MATLAB, or C++ Joy in dealing with
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integration of vehicles into mobility and energy systems. We improve the efficiency, sustainability and economics of electric vehicles by optimizing and accelerating the integration of components up to complex