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Field
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understanding of artificial intelligence applications and methodologies, such as working knowledge of generative AI tools, use of large language models, machine learning, and ethical frameworks for AI
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robotic tools at Ames National Laboratory and develop new methodologies on high-throughput experimentation or artificial intelligence-enabled self-driving labs. The successful candidate must be able
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, artificial intelligence, and cosmology. Research Opportunity These positions are an opportunity to join Professor Benjamin D. Wandelt as he establishes a new research group at Johns Hopkins University
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 4 hours ago
/or machine learning/artificial intelligence algorithms. Projects may also include work focused on the analysis of spatial and geographic data and work extrapolating results to different spatial scales
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of Minnesota is seeking two postdoctoral research associates to join a team working on multiple research projects in the field of health data science, artificial intelligence and natural language process
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models Experience in artificial intelligence to develop the algorithms for digital twins Experience with both qualitative and quantitative data analysis techniques Experience in cleaning and analyzing
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University of Southern California (USC) | Los Angeles, California | United States | about 1 month ago
translational environmental health research. Our NIH-funded projects span environmental and molecular epidemiology, computational toxicology employing artificial intelligence, experimental studies (in vitro and
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understanding of artificial intelligence applications and methodologies, such as working knowledge of generative AI tools, use of large language models, machine learning, and ethical frameworks for AI
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 1 month ago
hydrologic model calibration, and use of artificial intelligence to improve existing methods in these areas. Topics related to model development include improvement of surface and groundwater hydrologic
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understanding of artificial intelligence applications and methodologies, such as working knowledge of generative AI tools, use of large language models, machine learning, and ethical frameworks for AI