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and systems and integration of R&D with alignment to ORNL and sponsor objectives. Collaborate with cross-disciplinary teams to integrate hardware and software solutions across different platforms and
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-scale scientific data. Publishing research in leading peer-reviewed journals and conferences. Researching and developing parallel/scalable uncertainty visualization algorithms using HPC resources
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Demonstrated research experience with HPC, AI/ML and/or distributed systems techniques. Proficiency in programming languages such as Python, C++, or similar, as well as experience with HPC environments and
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journals and conferences. Researching and developing parallel/scalable uncertainty visualization algorithms using HPC resources. Collaboration with domain scientists for demonstration and validation
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systems, high-speed parallel file systems, and archival solutions critical to advancing scientific discovery and innovation. As part of ORNL’s leadership-class computing ecosystem, you will play a vital
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Substance Abuse (WSAP) testing designated position. WSAP positions require passing a pre-placement drug test and participation in an ongoing random drug testing program. Why Join Us: This is an exciting
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power electronics resources modeling, explore different intelligence algorithms to enhance ease of usage of simulations, and different applications of EMT simulations. Selection will be based
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(ORNL). Multiple positions are available to support R&D with different research focuses. They include innovations in joining and materials processing/synthesis, AI/ML for process monitoring and control
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batch schedulers (e.g., SLURM, PBS, LSF) and parallel file systems (Lustre, GPFS/Spectrum Scale). Experience implementing and managing automation and configuration management frameworks (Ansible, Puppet
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. Demonstrated experience developing and running computational tools for high-performance computing environment, including distributed parallelism for GPUs. Demonstrated experience in common scientific programming