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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 days ago
Computer Science or EE/ECE on a topic in machine learning applied to natural language processing, computer vision, or a related area. Strong publication record in NLP, ML, or related areas -Strong
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, computer science, machine learning, and education research. Research Themes The research themes identified for the NTO postdoc include, but are not limited to, the following: Developing or evaluating methodologies
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want The postdoctoral research associate will be working on developing machine learning/artificial intelligence algorithms for various applications, including energy systems, health systems, and marine
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information here ! PURPOSE We are seeking a highly qualified researcher with a strong interest in applied statistics, machine learning, and artificial intelligence, with a particular focus on time-series
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campus. To learn more, go to Baylor Benefits & Advantages. Explore & Engage Learn more about Baylor and our strategic vision, Baylor in Deeds . Also, explore our great hometown of Waco and the many
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, molecular biology, and/or computational analyses. The postdoc will have the opportunity to guide the research of an undergraduate research assistant, if desired. Mentorship is a core mission of the Oldenburg
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management machine learning, distributed computing, and resource optimization leveraging the unique computational resources available at ORNL, including the Frontier supercomputer—the world's first exascale
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skills Excellent scientific writing ability and good communication skills Knowledge of scientific programming language(s), computer simulation, and quantum computing algorithms All tasks and job
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Cell Biology A working knowledge of computer software for data analysis and presentation. Experience with animal modes Preferred Qualifications: Background in perinatal biology Knowledge, Skills, and
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optimizing the squeezing of the vacuum to minimize quantum noise, a prototype cryogenic interferometer, using machine learning for nonlinear feedback control, devising techniques to quell opto-mechanical