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, Physics, or Chemistry. Knowledge of experimental fluid dynamics. Knowledge of mechanical engineering concepts and procedures. Computer and programming skills, including data processing and manipulation
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including engineering, economics, and environmental science. Experience developing mathematical or computational models for simulation and optimization of energy/economic systems in ASPEN Plus® and/or Julia
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engineering and nuclear-chemical engineering systems Create new reduced-order models and submodels related to the fluid flow, heat transfer, thermochemistry, and electrochemistry in multiphase systems Use
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The Multiphysics Computation Section at Argonne National Laboratory is seeking to hire a postdoctoral appointee. The successful candidate’s research will involve synergistic collaborations with a
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Qualifications: Ph.D. (completed within the past 0-5 years) in computer science, electrical engineering, applied mathematics, or a related field. Strong proficiency in Python, with additional experience in C, C
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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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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
Requirements Required skills, abilities, and knowledge: Recent or soon-to-be completed PhD (within the last 0-5 years) by the start of the appointment in computer science, electrical engineering, applied
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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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, 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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Electrical Engineering, Computer Science, Operations Research, or a closely related field. Experience in power systems, distribution systems, or microgrid modeling, with a solid understanding of advanced co