76 computer-science-programming-languages-"UCL"-"UCL" Postdoctoral positions at Argonne in United States
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The Chemical Sciences and Engineering Division is seeking applicants for a postdoctoral appointee who will conduct computational research in Selective Interface Reactions (e.g., atomic layer
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chemistry, materials science or related field; received within the last 5 years or upcoming year. Significant written and oral communication skills, as well as the ability to work in teams. Desireable
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of deposition science and heterogenous interfaces. Position Requirements: A PhD in chemistry, materials science or related field; received within the last 5 years or upcoming year. Significant written and oral communication
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nanofabrication. Experience in microwave and optical device characterization and measurement. Knowledge and good understanding of quantum information science. Experience with superconducting qubit design
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, engineering, or related field Comprehensive experience programming in one or more programming languages such as Python, C/C++ Experience with at least of one of the AI frameworks is required, such as PyTorch
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math, HPC, signal processing, computational physics and materials science. The appointee will benefit from access to world-leading experimental and computational resources at Argonne including some of
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(MSD), and Quantum Information Science (QIS) programs Disseminate results through high-impact publications and presentations at internal and external meetings Position Requirements Position Requirements
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may include work at Jefferson Lab, the Electron-Ion Collider (EIC) program, detector research and development, and applications of AI in nuclear physics. Applications received by Tuesday, November 4
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chemistry, chemical engineering, physics, computational science, materials science, or related field. Background in synchrotron characterization techniques. Experience collecting and analyzing large
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experience in economic and supply chain analysis, computational modeling, or policy analysis. Proficiency in scientific programming languages (e.g., Python, R) and data analysis libraries (e.g., pandas, NumPy