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dynamic and transient inverter modeling and different applications of the simulation. Selection will be based on qualifications, relevant experience, skills, and education. You should be highly self
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). Major Duties/Responsibilities: Develop physics-based, data-driven, and hybrid (physics-informed ML) models of thermal systems to capture dynamic thermal behavior Validate models against experimental data
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Requisition Id 16798 Overview: The Data and AI Systems Research Section/Workflow systems Group within the Computer Science and Mathematics Division at Oak Ridge National Laboratory (ORNL) is
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-generation, data-driven manufacturing systems that integrate artificial intelligence, real-time sensing, and digital twins to transform how critical components are designed, produced, and qualified. The
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, including energy-efficient building systems, thermal-fluid processes, industrial heating applications, data center thermal management, and other emerging energy technologies. Develop and operate
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interferometry, volumetric accuracy assessment, spindle characterization, probing, thermal testing, or dynamic compliance testing. Experience integrating sensors, data acquisition systems, and
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partners, other research organizations, and universities related to advanced manufacturing technologies, and product, systems, and materials development. Responsible for presenting and reporting research
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, and data science to develop new methodologies for assessing and improving the quality of components fabricated using advanced manufacturing processes. This position resides in the Manufacturing Systems
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software that allow time-evolving models of complex systems to be calibrated against sparse, indirect, and uncertain observations. The group develops and maintains an open-source Python framework for
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leadership- class computing for science and engineering; focuses on grand-challenge science and engineering applications; procures largest-scale computer systems (beyond typical vendor design points) and