33 data-scientist Postdoctoral positions at Oak Ridge National Laboratory in UNITED-STATES
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of computational scientists, computer scientists, experimentalists, materials scientists, and conduct basic and applied research in support of the Laboratory’s mission. Engage with the broader community
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collaborative platforms like Flowcept, CrewAI, INTERSECT, and the S3M Facility API, pushing the boundaries in how scientists interact with real-time provenance data and AI-assisted experiments. Furthermore
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collaboration within a multi-disciplinary research environment consisting of mathematicians, computational and computer scientists, and domain scientists conducting basic and applied research in support of ORNL’s
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postdoctoral research associate to advance the state of scientific AI by addressing cross-cutting challenges in data readiness for AI to enable scalable, reproducible AI workflows on leadership-class systems
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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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environment consisting of mathematicians, computational and computer scientists, and domain scientists conducting basic and applied research in support of ORNL’s mission. Specific responsibilities include
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Requisition Id 15813 Overview: We are seeking a highly motivated postdoctoral researcher with a strong background in sensor integration, data acquisition, and in situ process monitoring
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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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laboratory investigations with inorganic mercury and methylmercury. Acquire and analyze data using a range of analytical instrumentation. Maintain detailed and accurate records. Prepare oral and written
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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