421 machine-learning-"https:"-"https:"-"https:"-"https:" positions at Carnegie Mellon University
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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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(e.g., Flask, Django, JavaScript) Machine learning fundamentals UI/UX design principles for prototyping Strong communication, analytical and problem-solving abilities. Excellent project management skill
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development (e.g., Flask, Django, JavaScript) Machine learning fundamentals UI/UX design principles for prototyping Strong communication, analytical and problem-solving abilities. Excellent project management
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Engineering, Software Engineering or similar Able to work an internship schedule during the summer 2025 semester Able to come on-site to the SEI Pittsburgh office Candidates will be subject to a background
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Engineering, Software Engineering or similar Able to work an internship schedule during the summer 2025 semester Able to come on-site to the SEI Pittsburgh office Candidates will be subject to a background
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. Excellent reasoning and problem-solving skills. Knowledge in machine learning and artificial intelligence methods and applications is a plus. Our benefits philosophy encompasses three driving priorities
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Designing and extending algorithms grounded in probabilistic machine learning Applying statistical techniques to assess robustness and generalization. Development of methods of research, testing and data
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of a computer monitor, extensive reading, transcribing, analyzing data and figures, visual inspection involving small defects, small parts and/or operation of machines, using measurement devices, and/or
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university’s creative, dedicated and close-knit community. We place emphasis on practical problem solving, interdisciplinary learning, a transformative spirit, and collaboration. The Human-Computer Interaction
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. Modeling dynamical systems Designing and extending algorithms grounded in probabilistic machine learning Applying statistical techniques to assess robustness and generalization. Development of methods