233 parallel-and-distributed-computing-"Multiple" positions at Oak Ridge National Laboratory
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cutting-edge requirements into resilient and scalable systems. The successful candidate will serve as a trusted technical advisor, systems architect, and subject matter expert across multiple classified HPC
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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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operational excellence and engagement with the communities where we live and work. ORNL invites you to apply to its Distinguished Staff Fellowship (DSF) Program. This program recognizes outstanding early-career
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! 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). The Emerging
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algorithms and parallel/distributed variational algorithms in AI/ML for application workflows and large-scale HPC and QC systems Develop quantum machine learning (QML) algorithms for optimization of multi
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Requisition Id 14889 Overview: We are seeking a Postdoctoral Research Associate who will focus on delivering groundbreaking computational chemical and materials science at the forefront
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Requisition Id 14778 Overview: The Nuclear and Radiological Protection Division (NRPD) at the Oak Ridge National Laboratory (ORNL) seeks an External Dosimetry Program Technical Specialist within
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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 expanding program at ORNL
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Requisition Id 14890 Overview: We are seeking a Postdoctoral Research Associate who will focus on applying computational methods in the areas of stimulus responsive separations and energy related
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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