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at the university campus in Stavanger. The core element of this PhD project is to use physics-based and data-driven modeling approaches for developing accurate models for real-time optimization and control
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autonomous systems, complex networks, data-driven modeling, learning control, optimization, and sensor fusion. The division has extensive collaborations both with industry and other research groups around the
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 4 hours ago
development of methods for chiral analysis of amino acids using CE-MS, and optimization of limits of detection. This initial research will utilize a newly installed SCIEX CESI 8000 capillary electrophoresis
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Pérez. The tasks to be carried out within the CPP2023-010861 project are: 1. Implementation of a real-time control system within the digital twin for optimal energy resource management. Different adaptive
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are escalated appropriately. Receives supply orders and confirms accuracy of delivery. May assist with cost control. Ensures that facilities and equipment are in optimal and proper working condition. Coordinates
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of sulfite-reducing spores by membrane filtration - optimization of the process to detect enterococci by the Enterolert DW method - implementation of the quality control method in accordance with ISO11133 Work
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++ and Python are required. Experience with control and optimization of power generation systems (e.g., wind power) is desirable but not required. Some experience with real-time control hardware is
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optimizing color selection for attentional purposes. The successful candidate will be required to design, program and conduct EEG-experiments, analyze and interpret EEG and behavioral data and present results
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quantitative predictions testable against empirical data from diverse ecological contexts. We use methods from theoretical evolutionary biology, including optimal control theory, life history modelling, adaptive
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AI-driven tools for bio-retrosynthesis-based metabolic pathway design, enzyme design and optimization, and DNA part selection. 2) knowledge-graph-based combinatorial experiment designs are used to span