429 data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"DFG-TRR" positions at Carnegie Mellon University
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, team and individual growth. CMU’s Computing Services’ Information Security Office is searching for a Principal Information Security Engineer/Incident Response Coordinator. This is an excellent
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to the Lead Financial Analyst, this role works closely with program and directorate leadership to ensure accurate financial information, sound planning, and strong financial stewardship in a compliance-driven
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, creative start-ups, big data, big ambitions, hands-on learning, and a whole lot of robots, CMU doesn’t imagine the future, we invent it. If you’re passionate about joining a community that challenges the
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, document, and maintain DR Plans with Computing Services and other CMU Technology departments for infrastructure, systems, data, security, and third-party systems. Exercises. Plan, facilitate, and document DR
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, creative start-ups, big data, big ambitions, hands-on learning, and a whole lot of robots, CMU doesn’t imagine the future, we invent it. If you’re passionate about joining a community that challenges the
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) where autonomous and human-guided agents interact with tools, data systems, and operators. AI test, evaluation, verification, and validation (TEVV) to improve confidence in performance, robustness
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, creative start-ups, big data, big ambitions, hands-on learning, and a whole lot of robots, CMU doesn’t imagine the future, we invent it. If you’re passionate about joining a community that challenges the
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, creative start-ups, big data, big ambitions, hands-on learning, and a whole lot of robots, CMU doesn’t imagine the future, we invent it. If you’re passionate about joining a community that challenges the
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, Academic Computing or Information Security; or if within a large college responsible for strategic IT support, planning, and direction. These are colleges that require significant IT resources to support
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models such as GPT and LLaMA, designing and deploying agentic workflows, as well as apply and advance traditional ML research and engineering across domains such as natural language processing, computer