49 computer-programmer-"St"-"University-of-St"-"St" Postdoctoral positions at Argonne
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lead efforts to develop experimental techniques using conventional and coherent imaging in the ultrafast time domain, as well as a computational framework for modeling and reconstructing images
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electrocatalyst materials Plan and execute in situ/operando studies using advanced techniques such as X-ray Absorption Spectroscopy (XAS), X-ray Photoelectron Spectroscopy (XPS), Raman spectroscopy, Differential
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focus on further advancing the ATTA technique. The Physics Division has an active and broad-ranging program at the intersection of nuclear and atomic physics including a strong focus on fundamental
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engineering principles Experience working safely with hazardous materials using engineering controls such as gloveboxes is desired. Knowledge of the use of computers to design and control experiments and to
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electrochemical methods such as cyclic voltammetry and electrochemical impedance spectroscopy is desired, but not required. · Experience working directly or collaboratively with computational methodologies
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methodologies and tools for economic and ecological analyses of hydropower systems. The position will involve the development and use of computer models, simulations, algorithms, databases, economic models, and
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techniques in interfacial science; and mathematical techniques and computer programming for data analysis. Considerable skill in working interactively and productively in a multidisciplinary environment Good
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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
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scientists with extensive microelectronics (materials and devices), AI, computational materials science and materials characterization expertise; and will be expected to bring the electrochemical expertise
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advanced computing, optimization, and data analytics technologies. The postdoctoral researcher will work with a team of researchers on solving challenging problems using optimization, stochastic models