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and assist in the development of novel separation and measurement protocols for complex nuclear matrices. Your work will support ORNL scientific staff conducting research and chemical operations
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for composites including injection molding (IM), compression molding (CM), thermoforming, and sheet molding compound (SMC) Lead and manage multifunctional materials research projects, including planning, execution
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manufacturing systems to enable simulation-assisted process monitoring and control Support research on advanced composite manufacturing processes such as thermoforming, compression molding, injection molding, and
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and edge computing; The design of architectures/models which accurately capture the complexities of the data, with robust estimates of confidence in predictions and compressed quantities of interest
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include data compression and reconstruction, data movement, data assimilation, surrogate model design, and machine learning algorithms. The position comes with a travel allowance and access to advanced
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fittings associated with a variety of systems including by not limited to steam, condensate, vacuum, compressed air, natural gas, laboratory gases, drain, waste, vent, process, potable, chilled and fire
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Science or a related technical discipline with a minimum of 2 years of technical experience in a lab environment. Safety mindset when handling compressed, fluorinated, and/or enriched gases. Motivated self
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, workflow, and data compression. Data Engineering — Engineering data assets and systems, including data wrangling and system design, to drive scientific innovation. Performance Engineering — Engineering 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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Science or a related technical discipline with a minimum of 2 years of technical experience in a lab environment. Safety mindset when handling compressed, fluorinated, and/or enriched gases Motivated self