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of molecular reactions occurring at the surface of various materials. In addition, computational fluid dynamics (CFD) simulations combined with microkinetic modeling will be carried out to study the heat
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The Center for Nanoscale Materials (CNM) at Argonne National Laboratory is seeking postdoctoral researchers to work on distributed quantum computing. The project aims to develop superconducting
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computer science or related computational engineering disciplines. Experience with simulation frameworks for complex computer systems and architectures. Some knowledge of accelerator (CUDA, SYCL, HIP) and scientific
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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, and carry out any required data analysis. Position Requirements • Experience working with Lorentz Transmission Electron Microscopy. • Strong background in Materials Science or Physics. • Min
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algorithms to develop cybersecurity, optimization, and control solutions for real-world grid applications. Candidates will be required to work in at least 4 of the following areas: Build, simulate, and
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of MEMS devices. Understanding the properties of materials used in MEMS and their compatibility with X-ray optics applications. Knowledge of using software tools to simulate the physical properties and
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The Postdoctoral Appointee will be part of an R&D group conducting use-inspired research supporting the development of process technologies for next-generation nuclear/chemical/electrochemical
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, in Electrical Engineering and Computer Science or related field obtained within the last five years. Experience with X-ray physics or optical wave modeling. Proficiency in programming with Python
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
, large-scale computational science, and simulation of networked physical systems Familiarity with techniques for sensitivity analysis and handling high-dimensional problems Experience in power grid