12 parallel-and-distributed-computing-phd Fellowship positions at Carnegie Mellon University
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duties as assigned. REQUIREMENTS: REQUIRED: PhD in in computer vision, machine learning, artificial intelligence, or a closely related field. Strong programming skills. Strong background in machine
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to healthier, cleaner, more efficient future for all. A research collaboration is being funded by the Energy and Environment Solutions (E2S) program of the Universite de Pau et des Pays de l’Adour (UPPA) and
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from multiple disciplines and institutions. Required: PhD in in computer vision, machine learning, artificial intelligence, or a closely related field. Strong background in machine learning / computer
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computational biologists. Publishing research findings in peer-reviewed journals and present at scientific conferences. Mentoring and supervise graduate and undergraduate students in related projects
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of Physics, Computer Science, Machine Learning, and Statistics, and enjoys close relationships with the University of Pittsburgh’s Department of Physics and Astronomy. Carnegie Mellon’s physics faculty hold
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fostering engaging and effective learning through the power of play. The ETC, a joint venture between CMU's School of Computer Science and College of Fine Arts, is renowned for its interdisciplinary, project
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fostering engaging and effective learning through the power of play. The ETC, a joint venture between CMU's School of Computer Science and College of Fine Arts, is renowned for its interdisciplinary, project
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conferences, e.g., ICRA, IROS Good oral and writing communication skills Completed Phd program Flexibility, excellence, and passion are vital qualities within the Robotics Institute. Inclusion, collaboration
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the full spectrum of advantages from comprehensive medical, prescription, dental, and vision insurance to an enticing retirement savings program offering a generous employer contribution. You can also
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or microworlds, conduct laboratory studies, and construct computational cognitive models including paradigms in Cognitive Science (Instance-Based Learning models) or AI (Reinforcement Learning). The fellow will