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and novel device technologies Develop, validate, and maintain simulation and modeling frameworks for detector performance, characterization, and benchmarking Analyze simulation results and experimental
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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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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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ML surrogate models for electronic structure and electrostatic potential in 2D materials Perform large-scale materials simulations (e.g., DFT, tight-binding, continuum models) to generate training and
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. This position is part of the DOE-BES initiative Integrated Scientific Agentic AI for Catalysis (ISAAC), a multi-facility collaboration integrating experimental measurements, simulations, and data science to
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. Quantum Mechanical Calculations: - Performing first-principles based or Density Functional Theory (DFT) calculations for molecules/materials and interphases - Utilizing Molecular Dynamics (MD) simulations
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models for microelectronics materials Curate, manage, and integrate heterogeneous datasets from experiments and simulations Collaborate closely with experimental teams to benchmark and refine computational
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methodologies and tools for economic and ecological analyses of hydropower systems. The position will involve the development and use of computer models, simulations, algorithms, databases, economic models, and
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. The postdoctoral appointee will work closely with multidisciplinary teams at Argonne and partner institutions and is expected to contribute to both methodological innovation and practical validation using simulation
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Applications are invited for post-doctoral positions in the Cosmological Physics and Advanced Computing Group (CPAC) Group in Argonne National Laboratory’s High Energy Physics (HEP) Division