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Field
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area of power systems with special interest in power system controls, protection, optimization, and AI/ML applications in power and energy systems. Experience with experiments and hardware-in-the-loop is
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mediators using in vivo mouse models. The position has a duration of two years. The project group is part of a vibrant and inclusive research environment (https://www.ous-research.no/kt/) at the Department
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, differential equations, geometry/topology, numerical analysis, optimization, and statistics. Part of the research is also carried out in close cooperation with other fields of science and technology at NTNU, as
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of capabilities and optimal solution architectures are not well understood. Current research identifies an active and growing research field, with numerous recent advancements. A focus on generative AI agents has
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main focus on the development of control software. ▪ You will design and implement advanced control and readout protocols and optimize experimental characterization workflow,s leveraging machine learning
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adaptation is crucial for optimal perfusion. In living systems, network architecture constantly changes in response to environmental stimuli towards uniform flow to optimize transport. Combining microfluidic
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 23 hours ago
diverse, respectful environment where our colleagues demonstrate professionalism, enhance learning, and create personal and professional sustainability. We optimize our partnership with the UNC Health
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 23 hours ago
, enhance 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
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network adaptation is crucial for optimal perfusion. In self-organizing life forms, network morphology constantly adapts in response to environmental stimuli towards more homogeneous distribu-tion of flow