80 application-programming-android Postdoctoral positions at Oak Ridge National Laboratory
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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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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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Requisition Id 16505 Overview: The Computer Science and Mathematics Division at Oak Ridge National Laboratory (ORNL) is seeking an exceptional Postdoctoral Researcher to advance programming systems
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understanding of parallel application development techniques (parallel programming models, algorithms, and software) Preferred Qualifications: Experience in implementing ab initio simulation codes such as VASP
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, reactor core, spent fuel, and fuel cycle applications through leadership in the development and analysis of SCALE and/or the Virtual Environment for Reactor Applications (VERA) simulations and in
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outcomes in peer-reviewed journals in a timely manner. Ensure compliance with environment, safety, health, and quality program requirements. Maintain strong dedication to the implementation and perpetuation
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harsh environment applications. Develop data acquisition and control systems that include hydraulic or pneumatic actuation and pressure monitoring combined with interrogation of optical fiber-based
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divisions and directorates with researchers and engineers to execute excising NNSA programs. Prepare and present periodic reports documenting research and development activities. Ensure compliance with
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, and adapt to ever changing needs. Special Requirements: Applicants cannot have received their Ph.D. more than five years prior to the date of application and must complete all degree requirements before
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Landscape analysis and modeling, with a focus on training and application of predictive machine learning tools. This researcher will synthesize regional-scale remote sensing imagery and ecological monitoring