462 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "Stanford University" positions at Carnegie Mellon University
Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
, 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
-
and/or interest in tools like: Proof Assistants Automated Verification AI Tools for Mathematical Theorem Proving Additional Information: Sponsorship: Carnegie Mellon is not a qualifying employer for the
-
, construction, bid, and closeout phases as well as analyzing and reporting of the overall project portfolio; (ii) collecting, managing, and analyzing data for implementation, improving processes, and reporting
-
unprecedented data sets with the potential to answer fundamental questions about the universe. At the same time, the flood of data will introduce new computational challenges. We are looking for full-stack
-
, 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
-
, 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
-
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
-
, 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
-
, 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
-
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