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appointment is for one year, renewable for a second year pending satisfactory performance and availability of funding. Research topics of interest include numerical methods for scientific machine learning and
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focus on developing play-based learning resources and interdisciplinary multimedia projects, with some aspects overlapping with formal STEM education and policy. In addition to project responsibilities
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 3 hours ago
to): Develop machine learning algorithms that utilize fire products from geostationary satellites to better represent fire evolution and variability Develop machine learning emulators to represent forward
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Bilingual in English and Spanish and/or Haitian Creole preferred Experience working with big data, machine learning preferred Department Specific Functions The CRANE Lab, within the University of Miami Miller
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-efficient machine learning and model compression Applications of AI for circular economies Sustainable AI for the smart home Intelligent residential energy aggregation for virtual power plants Trustworthy and
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. Experience working with a high-performance computing (HPC) environment. Familiarity with machine learning and advanced statistics. Experience with analysis of time series data from intracranial EEG (iEEG
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samples. • Sufficient knowledge of mathematics and statistics is required to analyze and interpret test results. • Knowledge and skill sufficient to maintain and operate standard instruments (qPCR machines
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tissues. Dr. Emfinger is looking to recruit Postdoctoral Scholars interested in islet biology and machine learning. The Postdoctoral scholar will have the opportunity to collect data, analyze large datasets
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, Materials Science, Engineering Mechanics, Manufacturing Engineering, Mechanical Engineering, Artificial Intelligence/Machine Learning, or a related field completed within the last 5 years Preferred
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participant outcomes. The project will use a variety of approaches, including human perceptual experiments, machine learning, digital signal processing, and computational models of hearing. UConn has a vibrant