43 programming-"https:"-"Inserm"-"FEMTO-ST" "https:" "https:" "https:" "https:" "RAEGE Az" Postdoctoral positions at Oak Ridge National Laboratory in United States
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(HPC), or large-scale data analysis. Experience in applying AI/ML techniques to hydrological and Earth sciences. Proficiency in scientific programming languages such as Python, Julia, R, Fortran, or C/C
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management, workflow systems, analysis and visualization technologies, programming systems and environments, and system science and engineering. Major Duties/Responsibilities: The position requires
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to ORNL's Research Code of Conduct. Our full code of conduct and a statement by the Lab Director's office can be found here: https://www.ornl.gov/content/research-integrity . Basic Qualifications: PhD in
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Requisition Id 15408 Overview: Oak Ridge National Laboratory (ORNL) (https://www.ornl.gov/) is the largest US Department of Energy science and energy laboratory, conducting basic and applied
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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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(https://www.olcf.ornl.gov/frontier ) and plant phenotyping (https://www.ornl.gov/appl ). GPTgp is a pilot project initiated in September 2025 with funding from the US Department of Energy and will
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. Supporting the largest radioisotope production and research portfolio within the Department of Energy (DOE) Office of Science for Isotope R&D and Production, as well as extensive isotope production programs
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, health, and quality program requirements. Maintain a strong commitment to the implementation and perpetuation of values and ethics. Deliver ORNL’s mission by aligning behaviors, priorities, and
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research findings at conferences, program reviews, and technical meetings Ensure compliance with environmental, safety, health, and quality program requirements Deliver ORNL’s mission by aligning behaviors
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. Demonstrated experience developing and running computational tools for high-performance computing environment, including distributed parallelism for GPUs. Demonstrated experience in common scientific programming