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collaborators across institutions to enable integration of scattering-derived insights into physics-informed AI models. Document research results, contribute to publications in peer-reviewed journals, and present
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environmental trade-offs. Contribute to projects involving capacity expansion, production cost modeling, and equilibrium modeling of power systems. Design and apply mathematical optimization models, including
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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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) simulations and reduced order modeling of turbulent and reacting flows relevant to advanced propulsion and power generation systems, such as gas turbines and detonation engines. The successful candidate’s
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field Strong foundation in electrochemistry, electrochemical engineering, and chemical processing Demonstrated experience in mathematical modeling of electrochemical systems; knowledge of solid mechanics
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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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We are seeking a highly motivated postdoctoral researcher to conduct independent research on foundation models for scientific and engineering applications, with an emphasis on training, adaptation
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modeling and techno-economic assessment as appropriate. The candidate will work independently under general guidance, collaborate effectively within a multidisciplinary team environment, and prepare
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and integrate emerging AI techniques (e.g., agentic workflows, LLMs) into scientific problems, ensuring methods effectively solve real domain challenges. Advanced Model Development: Design and debug
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, Earth system science, applied mathematics, or a related field. Experience with one or more coastal/ocean modeling systems (e.g., MPAS-Ocean, ADCIRC, ROMS, NEMO, WAVEWATCH III) and familiarity with