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. Development of real-time optimization algorithms and model predictive control (MPC) strategies for adaptive process management. Addressing data sparsity and data quality issues in industrial process data
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 month ago
world. Position Summary The postdoctoral researcher will conduct advanced research in artificial intelligence (AI) and machine learning, with a focus on developing novel algorithms and systems. The position offers
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computing), EMT simulations, and power electronics control. Major Duties/Responsibilities: Develop electromagnetic transient (EMT) models for transmission or distribution grids, synchronous generators, large
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Postdoctoral Research Associate in the Department of Computer Science with a particular emphasis on the design and performance analysis of resource allocation algorithms for entanglement distribution in quantum
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will contribute to high-impact projects, including: 1. Developing and validating algorithms that extract data from the Epic EHR (e.g., large language models) via comparison with manually extracted data
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, algorithms and products: undertaking advanced research activities addressing major observational gaps and scientific priorities in EO. The research will cover a wide range of innovative topics and missions
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, analyse, and validate innovative numerical algorithms and mathematical frameworks for problems arising in materials, fundamental physics, dynamics, optimisation, control, uncertainty quantification, inverse
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AI Algorithm and Autonomous Decision-Making Systems RESPONSIBILITIES Research and develop autonomous decision-making algorithms for process industries (e.g., chemical, pharmaceutical, materials, energy
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Develop industrial process digital twin models based on the fusion of mechanistic and data-driven approaches. Develop predictive maintenance and fault diagnosis algorithms for critical equipment (e.g
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, reliability, and consistent behavior. Learning-based controllers can achieve high performance in complex and uncertain environments, yet ensuring predictable operation under distribution shifts, sensor noise