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to support AI research workflows. Design and implement efficient AI workflows optimized for KSL's high-performance computing environment. Build and maintain secure, OCI-compliant, HPC-ready container images
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issues. The role ensures reliable operation of desktops, laptops, peripherals, and related systems, while maintaining high service standards and contributing to continuous improvement of end-user support
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Position Summary Serve as the Lead for the team ensuring smooth operation of the Linux cluster consisting of 300+ GPU/CPU compute nodes including parallel filesystems and high-performance network
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endpoints, physical scientific workstations, and virtual scientific workstation services. This role enables secure, reliable, and high-performance access to scientific desktop environments for faculty
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ticketing system, the candidate is expected to provide advanced support in computational science and engineering, big data analysis, machine learning, or any related field. Senior candidate should initiate
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to gather requirements, manage expectations, and balance competing priorities. Experience supporting high-performance or GPU-enabled scientific computing environments, including NVIDIA/CUDA, performance
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available in the Materials Science and Engineering & Applied Physics Program. This position focuses on materials for harsh environmental conditions (e.g., high temperatures, high pressures, and high-corrosion
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requires an expert who can architect modern high-performing, secure cloud and hybrid integration platforms while actively writing code, creating reusable frameworks, and mentoring engineering teams. You will
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hardware tracking processes and updates the asset register, collaborating with various teams to meet procurement and regulatory requirements while maintaining high standards of security and operational
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devices Design intuitive interfaces for AI model interaction and advanced image analysis Manage high-performance databases optimized for large-scale imaging datasets Implement security measures including