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in materials for electrochemistry. While the focus in on computational expertise, this position will involve some experimental work in adapting workflows for automation and artificial intelligence
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years ) Ph.D. in Engineering, Operations, Computer Science, Mathematics or a related field. Knowledge of optimization, power systems operations and planning, electricity markets, issues surrounding
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capabilities. Key Responsibilities: Capturing requirements and analyzing specifications for future detector systems Performing conceptual design and system-level optimization using emerging computing
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, advanced computational techniques, and data science. The project involves: Materials Development Platform that will enable redox molecule optimization via predictive simulations, database management, and AI
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other collaborators for the development and optimization of experimental process; 2) analyze collected data with Argonne’s EverBatt model to estimate associated cost and environmental impacts; 3) write
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of Cyanobacteria and carrying out experiments with those bacteria, as well as flow cytometric analysis. Key Responsibilities: Develop and optimize extraction methods for recovering ultra-long, high molecular weight
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define requirements and performance specifications for future HEP/NP detector systems Perform detector concept development, system-level design, and optimization leveraging emerging computing architectures
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advanced computing, optimization, and data analytics technologies. The postdoctoral researcher will work with a team of researchers on solving challenging problems using optimization, stochastic models
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developing machine learning surrogates and emulators for dynamical systems. Proficiency in managing large datasets and training with GPU-enabled computing resources. Expertise in numerical optimization and
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computational research in accelerator science and technology. The focus is on developing and applying machine learning (ML) methods for accelerator operations and beam-dynamics optimization in advanced