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of production systems. The ETAC Group frequently uses automation and monitoring solutions to minimize our day-to-day maintenance and are always looking for opportunities to optimize system management practices
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emerging at the grid edge, providing essential services crucial to its reliable operation. Employing a diverse range of disciplines such as control theory, optimization, economics, game theory, data
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of the SAM.gov system or other database tools that may potentially interface with Ariba is required. Effectively interface with both internal and external stakeholders to ensure optimal supplier management and
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four categories: process understanding, process optimization, process prediction, and process control. The MSA group is within the Manufacturing Sciences Division (MSD), which conducts research
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on these topics. Basic Qualifications Ph.D. in Energy/Environmental/Natural Resource Economics or related Applied Economics discipline with a strong quantitative focus. Experience with quantitative optimization
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search out new technologies and techniques to improve design, workflow, and optimization of processes and performance management functions. Operate and communicate effectively and efficiently with all
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for opportunities to optimize system management practices or system performance. As the primary domain experts for these systems, you will work with technical staff to install and help tune the performance of various
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Azure related Power apps, including CoPilot Studio. Design and implement scalable AI systems, focusing on optimization, CI/CD pipelines, and model performance monitoring (e.g., LLM/GPT frameworks
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taking the lead in publishing high impact papers. Major Duties/Responsibilities: Work within a committed team of scientists to develop processing science of metals alloys through AMDED. Optimize process
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response Demonstrated expertise in process development/optimization for macro-scale deformation in AM Experience with multi-physics simulations on high performance computing (HPC) and maching learning (ML