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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
machine learning applied to natural language processing, computer vision, or a related area. Strong publication record in NLP, ML, or related areas -Strong programming skills, including TensorFlow and/or
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undergraduate and graduate degrees. Our fundamental interest is in the nature of language, how language is used, and how this use impacts language learning, processing, and structure over historical and
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with enhanced reactivity for medical and/or environmental applications. Such mini-catalysts are inspired on natural metalloproteins in which their reactivity is expanded by the concerted chemistry of
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the internal application process. Welcome to The Ohio State University's career site. We invite you to apply to positions of interest. In order to ensure your application is complete, you must complete
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or more projects, learning advanced cellular and molecular biology and anaerobic microbiology techniques. The candidate’s day will be split between benchwork to generate data, and computer work to generate
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public Contributions to laboratory management, including onboarding, safety, instrument maintenance, etc. are also expected Required skills and qualifications Doctoral degree/PhD in a relevant natural
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on large datasets, have experience conducting survey research online, and have experience working with natural language processing and application programming interfaces, as well as prompt engineering, large
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Job Code 9546 Employee Class Acad Prof and Admin Add to My Favorite Jobs Email this Job About the Job The Environmental Chemistry Laboratory at the Natural Resources Research Institute (NRRI) is seeking
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to significantly extend our existing team’s capabilities for data scoring and analysis (e.g., with expertise in natural language processing, machine learning, or computational modeling). Finally, the
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of natural language processing, machine learning, artificial intelligence, and human-computer interaction. Established within the School of Computer Science, LTI pioneers innovative approaches to understanding