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) at Oak Ridge National Laboratory (ORNL). This project will be focusing on the development of advanced Artificial Intelligence (AI)/Machine Learning (ML) tools for the measurements of 3D tensorial strain in
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sciences, computer science, machine learning, and education research. Research Themes The research themes identified for the NTO postdoc include, but are not limited to, the following: Developing
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agriculture. Developments in remote sensing, computer science and biogeochemistry support visions of cost-effective and reliable “natural climate solutions”. At the same time, there are hot technical and
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information, remote sensing data, and GIS software. Experience in deep learning and computer vision. Experience in developing software tools and products. Experience in writing scientific papers and successful
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 months ago
Computer Science or EE/ECE on a topic in machine learning applied to natural language processing, computer vision, or a related area. Strong publication record in NLP, ML, or related areas -Strong
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 23 hours ago
Computer Science or EE/ECE on a topic in machine learning applied to natural language processing, computer vision, or a related area. Strong publication record in NLP, ML, or related areas -Strong
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simulations of reactor core, and other system components Develop reduced-order calibration approaches and apply machine learning and Bayesian calibration methods to enable multi-scale, multi-physics model
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. Discipline(s): Business (4 ) Chemistry and Materials Sciences (12 ) Communications and Graphics Design (4 ) Computer, Information, and Data Sciences (17 ) Earth and Geosciences (21 ) Engineering (27
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practitioners. The Fellow will also teach one course per year. Throughout the fellowship period, the Fellow will work alongside other Post-Doctoral fellows at GRI and participate in a professional development
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would include: Co-developing a hybrid machine learning/process-based model of anaerobic digestion processes Performing techno-economic and lifecycle analysis of microgrids build around novel biogas-fueled