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into scalable, high-performance code. Participants will have the opportunity to learn to apply and hone these skills and acquire additional ones as they work on real-world problems. Examples of Research Areas
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and often different from the canonical types of data used to benchmark machine learning (ML) algorithms. In this opportunity, we will be evaluating how state-of-the-art ML techniques can be used
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, data engineering, data analytics, artificial intelligence, machine learning, deep learning, natural language processing, and automation using modern tools and techniques. During this fellowship, you will
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to identify key uncertainties in estimating direct data center water use, including development of reproducible data extraction and documentation approaches; and Develop and evaluate a regional machine learning
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gaps in dose-selection methodologies to support regulatory decision-making and future pediatric drug development strategies. Learning Objectives: You will meet regularly with your FDA mentor and a
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of Yuhua Duan. This project will be hosted at the NETL Pittsburgh, PA campus. Although material modeling with artificial Intelligence/machine learning (AI/ML) applications and experimental instrumental
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to complement your education and support your academic and professional goals. Along the way, you will engage in learning activities and research in several areas. These include, but are not limited to: Assess
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) framework to assess biological risks associated with blast overpressure (BOP) from military weapon systems. You will engage in research and applied computational activities to model blast-induced energy
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reports/visualizations and presentations, and collaborating with multidisciplinary teams. Learning Objectives: You will train with CDC’s Center for Forecasting and Outbreak Analytics, gaining hands
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. Additional Desired Qualifications: Demonstrated success in collaborative environments. Experience with NASA remote sensing data and machine learning. Experience communicating scientific concepts to wide