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tools such as Bash, Python, or Ansible. Experience with performance tuning and benchmarking tools for HPC environments (e.g., Ganglia, Grafana, or similar). Experience with parallel programming frameworks
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leading peer-reviewed journals and conferences. Researching and developing parallel/scalable uncertainty visualization algorithms using HPC resources. Collaboration with domain scientists for demonstration
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and programs to support operations, monitoring, and automated administrative tasks. Provide senior-level guidance to establish technical best practices, performance standards, and operational procedures
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targeting large-scale computational resources that involves numerical methods, parallel algorithms, inter-process communication and synchronization, and at least one traditional high performance computing
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deploy solutions on HPC and QC. Oversee, manage, facilitate, and catalyze partnerships in the user programs that provide access to the leadership computing facilities that include classical and quantum
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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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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 for their needs
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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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neural networks, including CNNs, GANs, transformers, and GNNs for urban science applications. Expertise in programming languages for software development and data management with proficiency in Python, SQL
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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