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performance, and data and product quality. You will join the section in charge of sensor performance, data quality, algorithm development, and calibration and validation (Cal/Val) for the ESA EO missions
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 6 days ago
to the development and validation of computational methods that integrate images with other multimodal data. The postdoctoral research associate will design, implement, and evaluate algorithms and models
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 17 hours ago
to the development and validation of computational methods that integrate images with other multimodal data. The postdoctoral research associate will design, implement, and evaluate algorithms and models
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. Subject description Automatic Control comprises the analysis and synthesis of models and model-based algorithms for control, estimation, and monitoring of complex dynamic systems. Project description
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Assistant (RA) or a Postdoctoral Research Associate (PDRA). The appointed candidates will support advanced research initiatives focusing on systems design, distributed systems, and algorithmic optimization
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employees, including 120 teachers and 120 PhD students. Approximately 5,000 undergraduate students take one or more courses at the department each year. You can find more information about us on the
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will also investigate process optimisation algorithms, providing a route toward autonomous optimisation and ultimately enabling long term stable operation under variable load conditions. This post is
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classification of aluminium scraps and contaminants. Design and validate algorithms for multi-sensor data interpretation and sensor fusion. Conduct laboratory experiments on scrap characterisation and sorting
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University We are looking for a highly motivated postdoctoral researcher with a strong interest in optimization. The position will involve the development of novel reformulation and algorithmic methods
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of two years. About the Project The successful candidate will advance the algorithmic and theoretical foundations of reinforcement learning applied to complex, high-dimensional dynamical systems