236 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "U.S" "U.S" "U.S" "U.S" positions at Oak Ridge National Laboratory
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workflows, and data infrastructure to accelerate discovery in Populus genomics and the characterization of Populus-associated microbial communities. The successful candidate will design and implement scalable
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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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related experimental data. This position resides in the Neutron Scattering Division, Neutron Sciences Directorate at Oak Ridge National Laboratory (ORNL) and is embedded in the MAIQMag (Multimodal AI
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://www.ornl.gov/directorate/isotopes for more information about ISED. About ORNL: As a U.S. Department of Energy (DOE) Office of Science national laboratory, ORNL has an impressive 80-year legacy of addressing
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capabilities in a wide range of areas, including applied mathematics and computer science, experimental computing systems, scalable algorithms and systems, artificial intelligence and machine learning, data
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experience. Understanding of biogeochemical and ecological processes. Programming experience in Fortran, python, R, or a related language. Experience in geospatial and/or time series data analysis. Evidence of
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, security and data integrity across compute and storage systems Lead operating system and third-party software maintenance efforts, balancing security requirements with research uptime Design and implement
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Requisition Id 15598 Overview: As a U.S. Department of Energy (DOE) Office of Science national laboratory, ORNL has an impressive 80-year legacy of addressing the nation’s most pressing challenges
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/or Python for model development, automation, signal processing, and large-scale data analysis. Active or eligible for a U.S. Department of Energy (DOE) Q clearance. Special Requirements: Visa
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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