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such as analyzing time series data for anomaly detection and classification Experience in data fusion and data correlations using orthogonal sensor streams Experience adapting and optimizing data science
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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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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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knowledge of key AI methods such as deep learning, operator learning, and Bayesian optimization, and apply it to develop next-generation surrogate models. This position will enable you to coordinate and
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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
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to the development and optimization of strategies for proton polarization using DNP techniques for structural analysis. Publish scientific papers resulting from this research and present results at appropriate
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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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-disciplinary team to develop appropriate models and computational strategies to assess HFIR Isotope Production target design. Contribute to the design of radioisotope production targets to optimize coolant flow