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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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including engineering, economics, and environmental science. Experience developing mathematical or computational models for simulation and optimization of energy/economic systems in ASPEN Plus® and/or Julia
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of urbanization on precipitation, and aerosol-cloud interactions Strong modeling skills and high-performance computing experience Experience with model code development, and strong programming skills (e.g., Fortran
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The Mathematics and Computer Science Division (MCS) at Argonne National Laboratory is seeking a Postdoctoral Appointee to conduct cutting-edge research in scientific machine learning, focusing
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collaborators as well as various experimental and computational groups at CNM, at Advanced Leadership Computing Facility (ALCF) and the Computational Science Division (CPS) division at Argonne. The postdoctoral
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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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team that focuses on materials for classical microelectronic interfaces and quantum information science. The group actively interacts with the broader Argonne and UChicago community of scientists as
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Intelligence, Machine Learning, Quantum Information and Quantum Simulation. The successful candidate will be expected to lead an independent research program in particle theory to strengthen and complement
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The Chemical Sciences and Engineering Division at Argonne National Laboratory is seeking a Postdoctoral Appointee to conduct innovative research focused on the synthesis, recycling, and performance