461 computer-science-intern-"https:"-"https:"-"https:"-"https:" positions at Carnegie Mellon University
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Details Posted: Unknown Location: Salary: Summary: Summary here. Details Posted: 18-Mar-26 Location: Pittsburgh, Pennsylvania Type: Full-time Categories: Staff/Administrative Internal Number
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the engineering team in the Biorobotics lab. Conduct original research and help develop new methods. Identifies problems and obstacles to progress; develops strategies to solve problems. May program software in
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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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of computer graphics, human-computer interaction, computer vision, and machine learning. Conducting comprehensive literature reviews in related areas, including deep generative models, image and video synthesis
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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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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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extracurricular activities (e.g., reading groups, internal talks, technical sharing) and contribute to a strong technical culture. Requirements Education / Experience: BS in Electrical Engineering, Computer Science
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political attitudes, reducing belief in conspiracy theories, and, more recently, increasing belief in them. The research sits at the intersection of AI safety and behavioral science, examining both
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with researchers, government customers, and other engineers, and contribute to technical strategy for the lab. Required Qualifications B.S. in Computer Science, Electrical Engineering, Statistics
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resource in software engineering, computer security, and process improvement. The SEI works closely with defense and government organizations, industry, and academia to continually improve software-intensive