564 engineering-computation "https:" "https:" "https:" "https:" "Univ" positions at North Carolina State University
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experience ($67,500 - $71,000) Work Schedule M - F, 8:00 - 5:00 (flexible work arrangements may be approved for this position) Job Location Raleigh, NC Department Computer Science Engineering About the
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buildings/classrooms spread across both campuses, capturing and/or streaming live on-campus classes, assisting faculty with computer applications immediately during live lecture capture classes, and ensuring
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Technology Loan Program in rural, high-need areas, and 4) Broader Impact Support that helps NC State faculty in developing Impact Identities and carrying out broader impacts activities integrated with
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expertise of multiple specialists utilizing a team approach to patient health care. For more information about the NC State Veterinary Hospital go to https://hospital.cvm.ncsu.edu/ The NC State Equine
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Libraries, please see http://www.lib.ncsu.edu/aboutthelibraries/ The Acquisitions & Discovery (A&D) department supports the teaching and research program of the University by providing searchable metadata
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, please go to https://jobs.ncsu.edu/postings/223844 . NC State University is an equal opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without
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all employees to reach their fullest potential at work. As you consider this opportunity, we encourage you to review our Employee Value Proposition (https://news.hr.ncsu.edu/you-belong-here/ ) and
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AM -5:00 PM Job Location Raleigh, NC Department Department of Materials Science and Engineering About the Department The Department of Materials Science and Engineering at NC State is recognized as one
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, Model Serving/Inference, and Monitoring. Technology Selection: Evaluate, select, and integrate appropriate cloud-native services (AWS, Azure, or GCP), hybrid and on-prem computing resources, and open
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/CloudFormation) for provisioning and managing all underlying compute, networking, and storage resources (e.g., Kubernetes clusters, GPU instances). Feature Engineering: Define shared data and feature management