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Scheduled Hours 40 Position Summary Assists in application development and integration on our High-Performance Computing (HPC) cluster used by researchers across disciplines. Work closely with
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Operate, repair, troubleshoot, control, and maintain, high pressure boilers, valves, traps, expansion joints, piping systems, auxiliary equipment, and distribution systems on University owned
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develop software for high-energy particle physics. Optimize software for performance, scalability, and efficiency on modern computing architectures, including HPC and distributed systems. Participate in
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, prompting strategies, and retrieval systems for high-stakes environments Conducting pilot evaluations with judicial partners to study how AI tools perform in real decision-making workflows, and translating
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to monitor alarms. Reapplies pulse ox probe. Specimen Collection Performs point of care testing; maintains and calibrates equipment and supplies. Collects specimens, including urine, stool, sputum and swabs
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to monitor alarms. Reapplies pulse ox probe. Specimen Collection Performs point of care testing; maintains and calibrates equipment and supplies. Collects specimens, including urine, stool, sputum and swabs
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overseeing front-line arborist staff in the field. Responsibilities include time and leave approvals, performance management, administration of the shop safety program, work scheduling through the CMMS
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, servers, and email systems; installs, configures, and repairs personal computer hardware and software systems; and performs related work as required. SUPERVISION RECEIVED AND EXERCISED Receives general
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candidate with a visionary approach to the tight integration of cutting-edge high-performance computing (HPC) and research software engineering (RSE) with the highly dynamic MDC research environment. What we
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The University of North Carolina at Charlotte | Charlotte, North Carolina | United States | 12 days ago
and relevant work experience. Preferred Education Skills and Experience: Experience in High Performance Computing related technologies such as schedulers, parallel computing, storage systems