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diagnosis of gas turbines. The project focuses on developing an integrated approach that combines machine learning techniques with physics-based models to estimate the health of various system components
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(SHM), physics-based modeling, and data-driven analytics to enable predictive, performance-based decision-making and improve infrastructure safety, resilience, and lifecycle performance. The candidate is
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advanced plasma diagnostics, plasma-based surface treatments, and surface characterization, with theoretical work focused on the modeling of such discharges. The PhD topic proposed here contributes
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at this time, unless they are Legal Permanent Residents of the United States. A complete list of Designated Countries can be found at: https://www.nasa.gov/oiir/export-control . Eligibility is currently open to
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general direction of the unit General Manager and within a centralized culinary model led by the Associate Director of Culinary. You are responsible for executing established menus, recipes, and culinary
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teaching in key and rapidly evolving areas such as autonomous systems, data-driven modeling, learning-based control, optimization, complex networks, and sensor fusion. Research at the division is
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. At the Division of Systems and Control , we develop both theory and concrete tools to design systems that learn, reason, and act in the real world based on a seamless combination of data, mathematical models, and
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) that represents entities such as people, projects, grants, publications, places, and outputs—and models their relationships over time. The position will build robust Python-based ETL/ELT pipelines, implement SQL
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. The project focuses on developing an integrated approach that combines machine learning techniques with physics-based models to estimate the health of various system components. The aim is that fault diagnosis
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computing infrastructure. The main tasks will include: designing, implementing and documenting programming components supporting experiments with AI models (including LLM, generative models, complex system