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for this postdoctoral position to work on development and scaling of the data infrastructure and software for AI applications on supercomputing systems and AI testbed systems. The postdoc will work on multimodal data
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
modeling of large-scale dynamics in networks. This role involves creating large scale models of dynamic phenomena in electrical power networks and quantifying the risk of rare events to mitigate
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contractors, are subject to particular restrictions related to participation in Foreign Government Sponsored or Affiliated Activities, as defined and detailed in United States Department of Energy Order 486.1A
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and heterointerfaces. The postdoc will lead experimental design, data acquisition, and quantitative reconstruction. The appointees will work within a highly collaborative team spanning multiple DOE user
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(HPC). The postdoc will work closely with visualization researchers, AI scientists, and domain application teams across Argonne and the broader DOE ecosystem. The goal of this postdoctoral position is to
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computational research. They are intrinsically driven, goal-oriented, and can work collaboratively with others. Working closely with the CPS divison, the postdoc will leverage AMReX and the LBM to develop
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novel machine learning models—including Physics-Informed Neural Networks (PINNs), variational autoencoders, and geometric deep learning—to fuse multimodal data from diverse experimental probes like Bragg
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, the postdoc will translate demonstrated prototype performance into a complete, buildable engineering specifications package for a scaled multi-element analyzer spectrometer and associated microscope/imaging
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) of electrochemical energy storage devices (diagnosis) and predict the SOH into the future (prognosis). The primary projects this postdoc will contribute to relate to lithium-ion batteries, advanced lead-acid batteries
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. The cosmology effort at Argonne includes staff members from the CPAC group, the Computational Science division, and the HEP Detector Group. The group also includes many postdocs, and a number of graduate and