80 engineering-computation-"https:"-"https:"-"https:"-"HFML-FELIX" Postdoctoral positions at Argonne
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Science and Engineering, Applied Physics, or a closely related discipline. • Demonstrated expertise in time-resolved X-ray diffraction and in-situ X-ray micro/nanoscopy. • Experience working with
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at a fraction of the computational cost. Recently Argonne successfully implemented, AERIS, a state-of-the-art seasonal-to-subseasonal (S2S) weather model AI model. A successful candidate will collaborate
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Extraction), jointly led by the Chemical Sciences and Engineering (CSE) and Applied Materials (AMD) Divisions at Argonne National Laboratory. This project focuses on understanding the evolution of structure
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, Quantum Information and Quantum Simulation. The successful candidate will be expected to carry out an independent and collaborative research program in particle theory that strengthens and complements
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multidisciplinary team, the candidate will work at the intersection of AI/ML, domain sciences, and high-performance computing. The role requires a strong foundation in LLMs and machine learning, along with
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on understanding novel and emergent behavior in nanoscale magnetic heterostructures, particularly in confined 2D van der Waals magnets and related devices. The goal of the program is to study and control magnetic
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Requirements Recent or soon-to-be-completed PhD (typically completed within the last 0-5 years) in chemistry, chemical engineering or materials science (those with other degrees but have similar skills to those
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collaborative effort across XSD, the Materials Science Division (MSD), and the Chemical Sciences and Engineering Division (CSE). Key Responsibilities: Develop and enhance pump–probe sub-nanosecond TXS method
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limited to, ATLAS at CERN, the South Pole Telescope, and the Simons Observatory. The candidate is also expected to work closely with computational experts at the Computational Science (CPS) division
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analysis Interdisciplinary Collaboration - Experience working in cross functional teams including molecular biologists, chemists, radiation experts and computational biologists Core Values - Ability to model