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with physics-informed neural networks, automatic differentiation, neural ODEs, or other physics-aware DL techniques. Skill in programming languages such as Python, C/C++, Go, Rust etc. Ability to model
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scholarly work or industry experience in economic and supply chain analysis, computational modeling, or policy analysis. Excellent oral and written communication skills in scientific and engineering contexts
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and oral communication skills Requirements: Recent or soon-to-be-completed PhD (within the last 0-5 years) in the field of organic, organometallic, or inorganic chemistry, or a related field Ability to
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The Chemical Sciences and Engineering Division at Argonne National Laboratory is seeking a Postdoctoral Appointee to conduct innovative research focused on the synthesis, recycling, and performance
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focus on our scientific program with CLAS12 (including the ALERT), Hall C and PRad-II at Jefferson Lab, and/or development of the EIC scientific program, including the development of a polarized light ion
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to microelectronics. The candidate will be part of a highly interdisciplinary project involving X-ray scientists, physicists, materials scientists, and computational scientists to solve challenging problems in
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. These instruments and techniques support APS user programs and beamline scientists working in materials science, geology, and biology. The brain is among the most complex structures known, containing over 89 billion
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at Materials Engineering Research Facility (MERF) and collaborators inside and outside Argonne. The candidate is expected to design and conduct experiments, analyze data and explore mechanisms behind
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computer vision. Experience with multi-modal data fusion and alignment techniques. Experience with spatial transcriptomics or other -omics data analysis. Proficiency in Python programming and scientific
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Quantum Theme, focusing on Next-Generation Quantum Systems. The successful candidate will lead efforts to discover and design quantum emitters with desirable properties for quantum information science (QIS