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Field
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and implement power grid planning/operations algorithms and tools and conducts data analysis related to energy and power systems, with emphasis on the following areas: Variable energy resource
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scale. Test methods for calibration corrections and noise reduction in retrieved data. Test algorithms for retrieval of sea surface temperatures from infrared radiances. Test algorithms for cloud masking
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, while contributing to development efforts from algorithm design and testing, synthetic data generation, user interfaces, and model deployment. Initial appointments will be for one year with
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. - Strong proficiency in machine learning, optimization algorithms, and computational modeling applied to construction systems. - Experience with designing and conducting experimental studies to evaluate
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Algorithms. The candidate is expected to conduct research in computer science focusing on the combinatorial aspects of quantum experiments and quantum algorithms for computational geometry problems. Prior
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the possibility of yearly renewal subject to funding availability. Responsibilities • Design and implement deep learning architectures, AI agent pipelines, and computer vision algorithms to achieve project goals
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 30 days ago
development of data processing tools. The position is for one year with the possibility of reappointment for an additional year. It will involve developing, implementing, and validating novel algorithms
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Science and Engineering, or a related area is required. The position will involve developing models and algorithms for the evolution of inorganic aerosols in the atmosphere, building upon the research
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-resolution dosimeter, and new algorithms. Following this, the candidate will parameterize a Monte Carlo-based dose calculation system (e.g., GATE, TOPAS, or Geant4-based simulation tools) for evaluation in
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learning, and AI-driven manipulation. This position offers the opportunity to work on real-world robotic systems and develop novel algorithms at the intersection of robot learning, control, and AI