343 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "U.S" "U.S" "U.S" "U.S" "UCL" positions at Oak Ridge National Laboratory
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open and transparent in communicating information to your groups and communicating staff achievements and changes to stakeholders in a timely manner. Working with Group Leaders to ensure staff actively
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supporting the management and oversight of the ORNL classification program and the classification of scientific, technical, and other information as well as provide Unclassified Controlled Nuclear Information
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data-model integration, leveraging the U.S. Department of Energy’s (DOE) Leadership-Class Computing Facilities to advance predictive understanding of complex environmental systems. Major Duties
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of emerging architectures and performance for advanced computing. This position resides in the Architectures and Performance Group in the Advanced Computer Systems Research (ACSR) / Comuter Science Mathematics
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; hold staff accountable for performance; lead regular technical group meetings; and review and certify the technical quality of proposals, publications, data and software releases, and other products
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development teams Basic Qualifications: A Bachelor's degree in Computer Science, Electrical or Computer Engineering, or other field relevant to the job duties with 2-4 years of relevant experience. Competency
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with data-driven modeling, including emerging approaches involving foundation models or scientific LLMs Special Requirements: This position requires the ability to obtain and maintain a clearance from
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Requisition Id 16168 Overview: The Environmental Sciences Division (ESD) of Oak Ridge National Laboratory (ORNL) has an opening for a Data Systems AI/ML Engineer within its Earth Sciences
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the production of intelligence information. Major Duties/Responsibilities: Conducts administrative investigations on incidents involving suspected or identified foreign intelligence activities: Conducts
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Laboratory (ORNL). As part of our team, you will investigate the atomic and electronic structures in energy and quantum materials and correlate them with relevant properties for energy and data storage