54 data "https:" "https:" "https:" "https:" "CNRS" "Univ" research jobs at Oak Ridge National Laboratory
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Director's office can be found here: https://www.ornl.gov/content/research-integrity . Basic Qualifications: A PhD in physics, chemistry, biochemistry or a related field completed within the last five years
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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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Acquisition Partner) for details. For more information about our benefits, working here, and living here, visit the “About” tab at https://jobs.ornl.gov . #LI-DC1 This position will remain open for a minimum of
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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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to commit 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
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array of capabilities in nuclear nonproliferation, data analytics, cybersecurity, cyber-physical resiliency, geospatial science, and high-performance computing, our organization seeks to produce world
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materials. In this role, you will develop and apply methods that integrate physics‑guided image correction with intelligent (AI/ML‑enabled) data‑acquisition strategies. Key objectives include (1) implementing
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and image data processing. Specific knowledge related to neural network design, training, and optimization is required. You will be joining a group with core expertise in sensor data analytics from
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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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length scales Develop machine learning algorithms to support process optimization, predictive modeling, and intelligent manufacturing control Integrate simulation tools with in-situ sensor data from