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at least one of: High-Performance Computing Distributed Systems Parallel Computing High Performance Algorithms Multiple Linux distributions · Experience with SLURM or similar HPC schedulers
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Qualifications Experience: Relevant programming experience developing, implementing, debugging, and maintaining applications with Python. Experience working with high performance computers (e.g., parallelizing and
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unique opportunity to engage in transformational research that advances the development of AI-ready scientific data, optimized workflows, and distributed intelligence across the computing continuum. In
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). Expertise in data and model parallelisms for distributed training on large GPU-based machines is essential. Candidates with experience using diffusion-based or other generative AI methods as
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of relevant experience in Linux systems administration or HPC systems engineering. Preferred Qualifications Demonstrated experience leading the design and deployment of HPC or large-scale distributed computing
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, academic-year position at the rank of Assistant Professor starting in Academic Year 2026-2027, with preference given to candidates specializing in Cloud/Cluster/Distributed Computing, Algorithms and Theory
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distributed computing for EMT simulations. • Experience with software development in Python, C++, or other programming languages. • Familiarity with GPU acceleration of numerical solvers, parallel sparse
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, operational intelligence, and natural-language interfaces that support distributed facility operations and improve reliability across U.S. ATLAS sites. In addition, the Lab provides comprehensive computation
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.) Experience with big data tools (e.g., Hadoop, Spark, Kafka, etc.), data pipelines, and software development frameworks Experience with parallel programming (High Performance Computing experience is a plus) and
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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