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in the areas of Hydrological and Earth System Modeling and Artificial Intelligence (AI). The successful candidate will have a strong background in computational science, data analysis, and process
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, including applied mathematics and computer science, experimental computing systems, scalable algorithms and systems, artificial intelligence and machine learning, data management, workflow systems, analysis
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, artificial intelligence and machine learning, data management, workflow systems, analysis and visualization technologies, programming systems and environments, and system science and engineering. Major Duties
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and understand the variation in plant phenotypic traits and response to stresses and link these to genetic information under the Center for Bioenergy Innovation project (https://cbi.ornl.gov/ ). Major
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. You will also assess the viability of accelerated irradiation methodologies (either using ions or research reactor irradiation data) for establishing performance envelopes for materials to be deployed
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physiologists, and data scientists to tackle fundamental issues in AI/ML-based photosynthesis research and applications. The selected scientist will have access to the world’s most advanced resources in computing
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systems, scalable algorithms and systems, artificial intelligence and machine learning, data management, workflow systems, analysis and visualization technologies, programming systems and environments, and
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safety at ORNL and DOE sites. This position resides in the Performance Engineering group in the Data and AI Systems Section in Computer Science and Mathematics division within Computing and Computational
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applied mathematics and computer science, experimental computing systems, scalable algorithms and systems, artificial intelligence and machine learning, data management, workflow systems, analysis and
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visual representation and analysis of large-scale 2D/3D scientific data. This position resides in the Data Visualization Group in the Data and AI Systems Section, Computer Science and Mathematics Division