49 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "Bournemouth University" Postdoctoral positions at Oak Ridge National Laboratory in United States
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and understand the variation in plant phenotypic traits and response to stresses and link these to genetic information under the Center for Bioenergy Innovation project (https://cbi.ornl.gov/ ). Major
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related experimental data. This position resides in the Neutron Scattering Division, Neutron Sciences Directorate at Oak Ridge National Laboratory (ORNL) and is embedded in the MAIQMag (Multimodal AI
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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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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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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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Application-driven Composable Distributed Storage. The candidate will be able to make research contributions in understanding and efficient use of distributed data storage and I/O subsystems for High
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strengths in high-performance computing, system architecture, and data analytics with applications in a large variety of science domains. NCCS is home to some of the fastest supercomputers and storage systems
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framework for driven and open quantum systems. Phenomenological modeling of dynamics/transport behaviors in complex systems, including strongly correlated electron systems. Experience in analyzing data from
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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