92 engineering-computation "https:" "https:" "https:" "https:" "https:" "https:" "https:" "UCL" positions at Argonne in United States
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The Center for Nanoscale Materials (CNM) at Argonne National Laboratory seeks a highly motivated postdoctoral researcher to join a multidisciplinary team advancing quantum information
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Postdoctoral Appointee - Investigation of Electrocatalytic Interfaces with Advanced X-ray Microscopy
5 years or soon-to-be-completed in physics, materials science, chemistry, chemical engineering, or a related field. Demonstrated expertise in synchrotron-based XFM or related X-ray microscopy methods
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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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The Chemical Sciences and Engineering Division is seeking a highly qualified and motivated postdoctoral researcher to join our team in the area of light-matter interactions, with a particular focus
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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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ionomer materials. Position Requirements Ph.D. completed in the past 5 years or soon-to-be-completed in chemistry, chemical engineering, materials science, or a closely related field. Strong background in
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(CO2) conversion processes 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 contribute
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symmetries, and nuclear data. LER also plays a critical role for the ATLAS National User Facility, where it provides support for ATLAS Users, conducts its own research program, and develops and operates
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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