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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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, and contributing to a robust data infrastructure that makes large-scale, multimodal datasets FAIR and AI-ready. You will publish findings in high-impact journals, present at major international
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design, develop, and evaluate AI-driven scientific visualization assistants that support intuitive, context-aware interaction with large-scale simulation and experimental data. The postdoc will focus
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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
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emphasize multi-wavelength survey science, the galaxy-halo connection, cluster cosmology, and large-scale cosmological simulations. Analysis efforts cover topics such as CMB power spectra, CMB lensing, galaxy
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for critical energy and technology sectors. Ability to assess the economic and operational impacts of large-scale AI adoption (e.g., data centers, compute infrastructure) on U.S. electricity demand, generation
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to contribute to other large-team scientific projects in materials engineering, chemistry, and beyond at Argonne National Laboratory. Position Requirements Required skills: Recently completed PhD (within the last
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., transformer-based models, tokenization, embeddings) to HEP analysis Communicate results internally and externally through talks, notes, and publications Position Requirements Recent or soon-to-be-completed PhD
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simulations, design and conduct experiments, and analyze multimodal data streams in a continuous, real-time loop with minimal human intervention (https://www.nature.com/articles/s41524-024-01423-2 , https
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and application of nonlinear x-ray spectroscopies. The successful candidate will work closely with experimental collaborators conducting measurements at large-scale x-ray user facilities, including