477 computer-science-intern-"https:"-"https:"-"https:"-"https:"-"UCL" positions at Carnegie Mellon University
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& Management to create a uniquely interdisciplinary learning environment. We empower learners to use data, technology, and analytical thinking to drive meaningful impact. Join our team as the Director of
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of experience, an MS with 8 years of experience, or a PhD with 5 years of experience in Computer Science, Electrical Engineering, or a related field. You’ve worked in a collaborative team environment as a
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, we want to hear from you! Requirements: BS in data science, machine learning, computer science, statistics, or related highly-quantitative discipline with eight (8) years of experience or equivalent
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securing catering, room reservations, summer campus housing, hotel accommodations, audio/visual technology, parking, web registration and many more customized services in support of events and conferences
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air quality, materials science, and data-driven decision support. As part of this effort, we are seeking a part-time Research Assistant to support data analysis, software testing, and research
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in computer science, statistics, machine learning, electrical engineering, or related discipline with ten (10) years of experience; OR MS in the same fields with eight (8) years of experience; OR PhD
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. Stakeholder Collaboration and Communication: Partner with internal stakeholders across program, contracts, and accounting functions to ensure coordinated financial management. Translate complex financial
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Carnegie Mellon University is a private, global research university that stands among the world’s most renowned education institutions. With ground-breaking brain science, path-breaking performances
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with internal partners to ensure smooth execution of visit schedules, room bookings, and related needs. Communication & Document Support: draft, proofread, and edit email correspondence, meeting notes
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. Adaptability, excellence, and passion are vital qualities within the Office of Human Resources. We are in search of a team member who can effectively interact with a varied population of internal and external