232 parallel-and-distributed-computing-"Meta"-"Meta" positions at Oak Ridge National Laboratory
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, and various geometry models (Computer Aided Design, unstructured mesh, Constructive Solid Geometry, etc.). Familiarity with established nuclear systems analysis software (such as SCALE, Nuclear Energy
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, Git, Azure Data Studio, pandas, NumPy, and Scikit-learn. Experience with High-Performance Computing (HPC) platforms with advanced skills in SLURM-based multi-node, multi-GPU training, data parallelism
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working with Infiniband and parallel filesystems (Lustre, GPFS) is a plus. Experience managing Linux/UNIX operating systems in a heterogeneous environment. Solid understanding of networked computing
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at ORNL! This position resides in the Emerging Technologies & Computing team in the Research Computing group in the Information Technology Services Directorate at Oak Ridge National Laboratory (ORNL
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ORNL and ESED project’s quality assurance requirements. The successful candidate will be responsible for the coordination of division documents through review, approval, and distribution with additional
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communities. You will work closely with a focused group of scientists, technicians, and engineers on ambitious, fast paced technical projects in support of the DOE Isotope Program. This has been a quickly
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languages. Experience using parallel Linux computing platforms, parallel job submission scripts, common software repository tools, and parallel visualization software. Preferred Qualifications: Excellent
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management machine learning, distributed computing, and resource optimization leveraging the unique computational resources available at ORNL, including the Frontier supercomputer—the world's first exascale
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utility production and distribution systems that provide utilities for buildings and facilities at UT-Battelle as well as other tasks as assigned my management. Utility systems include potable and process
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, MATLAB, Git, debugging, and modern software engineering practices. Experience with GPU computing (e.g., CUDA, HIP), parallel computing (e.g., MPI, Actor Model). Familiarity with containerization (e.g