50 computer-science-programming-languages-"U.S"-"U.S" Postdoctoral positions at Argonne
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preferred. Strong data analysis skills and ability in programming languages, such as Python, for performing experiments and analyzing data. Knowledge of innovative phase retrieval algorithms is desirable
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
The Mathematics and Computer Science (MCS) Division at Argonne National Laboratory invites outstanding candidates to apply for a postdoctoral position in the area of uncertainty quantification and
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is supported by a DOE-funded research program on ultrafast science involving Argonne National Laboratory, University of Washington, and MIT. The goal of this research program is to understand and
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The Chemical Sciences and Engineering Division at Argonne National Laboratory invites applications for a Postdoctoral Appointee position. The successful candidate will conduct research, under
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, computational science, a physical science, or engineering or related field. Comprehensive experience programming in one or more programming languages such as Python, C/C++. Experience with one of the AI
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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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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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. 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