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We invite applications for a Postdoctoral Appointee to contribute to a growing research program in process systems modeling and optimization for clean energy, critical materials, and advanced
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combinatorial techniques to evaluate the performance of synthesized catalysts, identifying promising candidates for further development Device-Level Performance Assessment: Integrate promising catalysts
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. This position offers an exciting opportunity to work at the intersection of HPC and AI, addressing critical communication bottlenecks and optimizing network interconnects for large-scale distributed systems
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Laboratory seeks a postdoctoral appointee to join a multidisciplinary team developing complex systems models, including agent-based models, and new algorithms and tools for machine learning and optimization
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data analysis/spectral image processing. Use of data analytics or machine learning to guide process design and optimization. Job Family Postdoctoral Job Profile Postdoctoral Appointee Worker Type Long
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algorithms to develop cybersecurity, optimization, and control solutions for real-world grid applications. Candidates will be required to work in at least 4 of the following areas: Build, simulate, and
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dynamics (CFD) to develop and optimize new processes and equipment designs using high-performance computing Analyze data, prepare manuscripts for submission to peer-reviewed publications, prepare technical
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modeling tools to develop and optimize new processes and equipment designs using high-performance computing Analyze data, prepare manuscripts for submission to peer-reviewed publications, prepare technical
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on integrating and analyzing diverse data types to support scientific discovery Research and implement data management solutions using advanced storage systems Evaluate and optimize AI applications for performance
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deployment, monitoring, and optimization of complex scientific data streaming workflows for current and future production infrastructures. The project will involve close collaboration with a team of systems