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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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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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of advanced bioleaching processes for recovery of critical minerals from secondary materials The candidate will design and execute experiments; operate, monitor, and troubleshoot bench- and pilot-scale
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is available for the design, licensing and operation of MSRs and other energy systems. Develop and perform laboratory tests and electrochemical operations with molten salts that may contain actinides
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. The researcher will develop and apply physical, chemical, and electrochemical models for advanced battery technologies and associated manufacturing processes. This work will quantify and explain relationships
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The Applied Materials Division, Process R&D and Scale up Group at Argonne National Laboratory is seeking a Postdoctoral candidate to conduct general research in material science and electrochemistry
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, asphaltenes, resins, and kerogen molecules and contribute to engineering design of upscaled processes. The candidate will be a part of the Applied Materials Division (AMD) within AET at Argonne and will
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following areas: Transition-edge sensors (TESs) or kinetic inductance detectors (KIDs) Cleanroom microfabrication processes, including: Thin-film deposition (e.g., magnetron sputtering) Electron-beam