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methods that aim to transform scientific discovery and leverage high-performance computing. Specifically, this will include research in : 1. Developing large-scale agent-based and other complex systems
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modeling. Perform predictive modeling using high-performance computing (HPC) infrastructure. Validate computational predictions by collaborating with experimental groups conducting reverse genetics studies
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and processing strategies aimed at achieving high performance, cost-effectiveness, and manufacturability. The selected candidate will leverage the capabilities of the Materials Engineering Research
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seeking a postdoctoral appointee to join our team focused on designing the communication infrastructure for next-generation High-Performance Computing (HPC) and Artificial Intelligence (AI) systems
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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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addition to collider physics, the position offers opportunities to engage in interdisciplinary research across Argonne, including projects involving artificial intelligence/machine learning (AI/ML) and high-performance
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of molecular reactions occurring at the surface of various materials. In addition, computational fluid dynamics (CFD) simulations combined with microkinetic modeling will be carried out to study the heat
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Argonne’s core values of impact, safety, respect, integrity, and teamwork Preferred Skills and Qualifications: Experience with high-performance computing and parallel computing Familiarity with data
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Laboratory. This is an opportunity to be part of a team helping with the design of new system software and runtime infrastructure to improve the performance and energy efficiency of future scientific computing