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Mathematics, or a closely related field. Design and optimize multimodal LLMs to encode, fuse, and reason over heterogeneous scientific data from diverse modalities such as numerical tables, text, and images
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imaging surveys Experience with computational astrophysics, including Python-based data analysis workflows Appointment Details The position is available beginning June 1, 2026, or earlier by mutual
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involvement in three SciDAC-5 projects: 1) Femtoscale Imaging of Nuclei using Exascale Platforms, 2) Fundamental nuclear physics at exascale and beyond, and 3) Nuclear Computational Low Energy Initiative
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design and build custom, non-commercial apparatus compatible with synchrotron scattering and imaging techniques at the Advanced Photon Source. Candidates with prior experience in developing operando
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, at scale. It will help us better understand and improve DAOS to meet the needs of AI-driven science applications. We expect the postdoc to help prototype, benchmark, and evaluate strategies to better support
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automation, high-throughput data acquisition, and real-time data processing, offering a unique opportunity to advance S/TEM capabilities, publish impactful research, and collaborate with a diverse group of
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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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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
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3 years) in computer science, materials science, chemistry, physics, mathematics or related engineering disciplines Knowledge of deep learning techniques for time-series and image data Experience with
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synchrotron-based techniques to inform process development. The role requires a strong background in synchrotron characterization techniques, mainly three-dimensional imaging (microtomography and