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, chunking, parallelization; Dask/Spark a plus). Experience using or building agentic/LLM-enabled workflows for data discovery, extraction, and normalization, with attention to provenance, reproducibility, and
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strategic management and strict adherence to security protocols. We are looking for candidates with extensive experience in either classified HPC data center operations, architecture, parallel computing
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partner with ORNL research organizations to enable research excellence and delivery. We work with other clustered computing and HPC groups to help research programs identify the best solutions
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systems. Expertise with batch schedulers (SLURM, PBS, LSF) and parallel file systems (Lustre, GPFS/Spectrum Scale). Proven ability to lead technical projects from concept through implementation, balancing
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environments. Leverage cloud object storage (e.g., Amazon S3) for data staging and artifacts; implement parallel, secure data movement and lifecycle policies. Basic Qualifications: Ph.D. in Computer Science
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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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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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environments Experience with parallel computing environments, HPC in a Linux environment Experience with surrogate modeling Experience with data analytics techniques Familiarity with C++ and GPU programming
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environments Experience with parallel computing environments, HPC in a Linux environment Experience with surrogate modeling Experience with data analytics techniques Familiarity with C++ and GPU programming
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Requisition Id 15939 Overview: We are seeking a Natural Resources Professional who will focus on conducting activities assigned to the ORNL Natural Resources Management Team (NRMT) by U. S