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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 12 hours ago
system and its top-level science objectives, but there has not been as much focus on connecting science objectives directly to the developmentof an engineered system. Systems engineering practices
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of knowledge-driven models, leveraging Bayesian statistics and causal inference for calibrated uncertainty, distribution-shift detection, and safety guarantees. You will be will working within the Center
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of knowledge-driven models, leveraging Bayesian statistics and causal inference for calibrated uncertainty, distribution-shift detection, and safety guarantees. You will be will working within the Center
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) for engineering systems and structures, as well as expertise in machine learning, stochastic modeling, and Bayesian statistics. Programming Skills: Proficiency in programming languages such as Python, C, or R
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, stochastic modeling, and Bayesian statistics. Programming Skills: Proficiency in programming languages such as Python, C, or R. Teamwork and Responsibility: Ability to work effectively within a project team
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–frequency representation (local stationarity, correlations, textures, extrema, anisotropy). This approach suggests leveraging the entire representation to define more robust detection and tracking criteria
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scientific in-house research agency with a mission to find solutions to agricultural problems that affect Americans every day from field to table. ARS will deliver cutting-edge, scientific tools and innovative
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: Genetic and developmental mechanisms of cardiovascular disease. Goals: Discover causal variants, understand congenital heart disease, and advance pharmacogenomics. Heart Failure Focus: Mechanisms and
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learning models, including their strengths, deficiencies, and strategies for (hyper)parameter optimization. Prior use of Bayesian optimization or other relevant active learning algorithms is preferred
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strategies to mitigate impacts on adjacent waters. Research activities include: coordinating with multiple stakeholders and collaborators to define objectives and research questions; leading participatory co