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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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decarbonization applications. With guidance, the appointee will: Develop advanced multiscale, multiphysics simulation tools applicable to the modeling of chemical processes and equipment relevant to chemical
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specifically on developing machine learning-based surrogates and emulators for the dynamics of power grids. This role involves creating advanced probabilistic models that capture the complex behaviors
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information Ability to model Argonne’s Core Values: Impact, Safety, Respect, Integrity, and Teamwork Desired skills, knowledge and abilities: Experience with large-scale molecular dynamics (MD) simulations
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applications. With guidance, the appointee will: Develop advanced multiscale, multiphysics simulation tools relevant to the modeling of processes involving combined nuclear, chemical, and electrochemical
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We invite applications for a Postdoctoral Appointee to contribute to a growing research program in process systems modeling and optimization for clean energy, critical materials, and advanced
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understanding of power distribution systems. Working knowledge of electric power distribution systems, DER operations, and grid modeling & simulation. Working knowledge of Git. Proficiency in Python and OpenDSS
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
: Expertise in rare event simulation, deep learning, and developing computationally efficient approaches for simulation and modeling in complex systems is highly desirable Experience with parallel computing
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The Applied Materials Division (AMD) in the Emergent Materials and Process Group at Argonne National Laboratory in looking for a Post-doctoral Appointee -- Pyrometallurgy. The candidate will perform
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running simulations or AI workflows on supercomputers Experience with training or applying large language models for research Experience with MPI and Input/Output (I/O), and data management Experience in