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The Argonne Leadership Computing Facility’s (ALCF) mission is to accelerate major scientific discoveries and engineering breakthroughs for humanity by designing and providing world-leading computing
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) or equivalent experience in a computational science discipline, computer science, or in a related field Strong programming skills in one or more scientific programming language, such as C++ and Python Experience
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multidisciplinary team, the Postdoctoral Appointee will work at the intersection of AI/ML, climate science, and high-performance computing. The candidate will develop LLMs specifically designed to understand, process
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
The Mathematics and Computer Science (MCS) Division at Argonne National Laboratory invites outstanding candidates to apply for a postdoctoral position in the area of uncertainty quantification and
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is supported by a DOE-funded research program on ultrafast science involving Argonne National Laboratory, University of Washington, and MIT. The goal of this research program is to understand and
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scientific programming language Experience with ML software such as Tensorflow and PyTorch Experience with ATLAS Software Development Ability to model Argonne’s core values of impact, safety, respect
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completed Ph.D. within the last 5 years in Computational Biology, Bioinformatics, Machine Learning, Artificial Intelligence, Virology, or a related field Strong programming skills in Python, R, or Julia, with
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, computational science, a physical science, or engineering or related field. Comprehensive experience programming in one or more programming languages such as Python, C/C++. Experience with one of the AI
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with physics-informed neural networks, automatic differentiation, neural ODEs, or other physics-aware DL techniques. Skill in programming languages such as Python, C/C++, Go, Rust etc. Ability to model
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scholarly work or industry experience in economic and supply chain analysis, computational modeling, or policy analysis. Excellent oral and written communication skills in scientific and engineering contexts