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and research in several areas. These include, but are not limited to: Adversarial location and network interdiction models Adversarial machine learning attacks and defense (e.g., against Bayesian
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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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Advisors: Kristen Okorn [email protected] (650) 960-5137 Questions about this opportunity? Please email [email protected] Qualifications Position Requirements: PhD in the physical sciences or engineering
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techniques. You will have the opportunity to participate in various projects utilizing artificial intelligence (AI) and machine learning (ML) to develop applications that optimize combat casualty care
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missions (e.g., Surface Biology and Geology - SBG). This could involve advancing atmospheric correction, dimensionality reduction, or machine learning approaches for handling big data in order to improve
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. The ideal candidate would have some, but not necessarily all, of the following: 1. A PhD in Chemical Engineering, Material Science, Chemistry or a related discipline; faculty member at an accredited college
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related area, including meteorology, hydrometeorology, remote sensing, surface and atmospheric modeling, or related fields. Experience in machine learning techniques are highly desirable. Please see https