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operational procedures. Cluster Management and Optimization: Oversee the installation, configuration, and management of HPC clusters, ensuring optimal performance, scalability, and reliability. Implement and
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, machining dynamics, metrology, and/or manufacturing process optimization. Analyze complex manufacturing problems using engineering fundamentals, experimental data, machine tool performance measurements
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, performance optimization, and lifecycle management. Demonstrated experience with Ansible, Python, Bash, automation, and infrastructure-as-code practices. Experience designing or integrating enterprise
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ensuring alignment with proper processes. Collaborate with the HPC engineering team to optimize solutions for performance and scalability in HPC environments. Collaboration with colleagues across
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the development and optimization of products for a variety of industries from automotive to aerospace made from new bio- and waste-derived plastic resins and fillers. The ideal candidate for this role would be
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efficient techniques that maintain robust privacy guarantees while minimizing performance impact. Additionally, you will optimize the balance between privacy and utility, addressing the challenges
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Requisition Id 16919 Annual Salary Range:$125,000.00 -$156,000.00 Work-Site Type: Remote ORNL offers a flexible work environment that supports both the organization and the employee. In addition
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, and Service. Promote equal opportunity by fostering a respectful workplace – in how we treat one another, work together, and measure success. Basic Qualifications: A Ph.D. in materials science and
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seeking a postdoctoral researcher with expertise in data management, workflow management, High Performance Computing (HPC), machine learning and Artificial Intelligence to enhance our capabilities in making
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Ridge National Laboratory (ORNL), under the mentorship of Dr. Nikki Thiele. As part of the Chemical Separations Group, you will have the opportunity to work with a multidisciplinary team comprising