50 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "Dr" "P" Postdoctoral positions 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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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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techniques; and (3) developing advanced methods for inelastic neutron scattering data analysis and workflow automation. The postdoctoral researcher will work in close collaboration with Dr. Raphaël Hermann and
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will involve designing beam dynamics experiments, measurement, simulation, and data analysis. This position resides in the Accelerator Physics Group in the Accelerator Science and Technology Section
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Postdoctoral Research Associate in the areas Artificial Intelligence (AI) for Integrated Hydrology Modeling. The successful candidate will have a strong background in computational science, data analysis, and
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with the Multiscale Dynamics and Heterogeneities in Quantum Materials themes at the CNMS and US DOE’s Genesis projects. The candidate is expected to work closely with Soumendu Bagchi and P. Ganesh. As
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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