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), at Oak Ridge National Laboratory (ORNL). As part of our team, you will ensure that the instrumentation and controls-based equipment associated with fiber and network systems utilized throughout the Oak
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advance the integration of observations and experiments into Earth system models across multiple scales. In particular, we are seeking a scientist with expertise in process-based modeling of biogeochemistry
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competing structural phases and the vibrational and electronic structure in materials with defects and disorder. This effort will further seek to implement strategies to leverage machine learning techniques
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process engineering in a research and development atmosphere. Projects range from creating new 3D models based on conceptual (whiteboard) designs and cleaning up legacy prints, to participating in large
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scheduling horizons with “Ready Backlog” work order. Facilitate the Weekly Scheduling Meeting to achieve a consensus between asset owners (i.e. Production and Engineering) and Area Team Leaders based
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in alignment with ASME NQA-1 and DOE directives. Ensure graded application of QA controls based on hazard categorization and risk. Provide QA support during design, procurement, fabrication
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to numerical methods for kinetic equations. Mathematical topics of interest include high-dimensional approximation, closure models, machine learning models, hybrid methods, structure preserving methods, and
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to Computational Methods for Data Reduction. Topics include data compression and reconstruction, data movement, data assimilation, surrogate model design, and machine learning algorithms. The position comes with a
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evaluate applications based on candidate excellence and relevance of the proposed research topic. ● Proposed Seaborg Researcher research project ○ Creativity and innovation ○ Impact on program’s mission
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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-motivated