152 machine-learning-"https:"-"https:"-"https:"-"Linnaeus-University" positions at Oak Ridge National Laboratory
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analytics that enhance and evolve business operations and scientific decision-making capability and related activities at ORNL.Qualified applicants will have a solid foundation of Generative AI and Machine
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toward integration of hydropower with battery storage and other technologies. Computational and analytical skills : Demonstrated ability in selecting and deploying machine learning tools (Random Forest
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to Computational Fluid Dynamics. Mathematical topics of interest include structure-preserving finite element methods, advanced solver strategies, multi-fluid systems, surrogate modeling, machine learning, and
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comparative research across Mojo, Julia, Rust, and vendor toolchains. Basic Qualifications: Ph.D. in Computer Science, Computer Engineering, or related field. Experience with LLMs or agentic AI frameworks
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to a general science-interested audience as well as a more scientifically trained audience such as researchers and sponsors. Should also have a firm grasp of standard business computer software (e.g
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Requisition Id 16025 Overview: The Advanced Engineering Technologies (AET) Group is seeking a dedicated individual to support our organization. The position will involve machine design and process
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Ridge National Laboratory (ORNL). This role will focus on the development and implementation of novel robotic construction workflows, human-machine collaboration strategies, and automated manufacturing
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Requisition Id 16186 Overview: The National Center for Computational Sciences (NCCS) at Oak Ridge National Lab (ORNL), which hosts several of the world’s most powerful computer systems, is seeking
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measurement activities to evaluate the mechanical and thermophysical properties of irradiated materials. Acquire, process, analyze, and report test data in accordance with applicable manuals, procedures, and
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, collaboration, inclusion and continuous learning. Stakeholder Engagement & Partnerships: Serve as the external interface for the center: liaise with sponsors (DOE, other federal agencies, industry, academia