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are seeking an postdoctoral appointee to contribute to this research to understand the underlying physics of spin and charge based memory materials using advanced in-situ transmission electron microscopy (TEM
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conventional and alternative energy sources, for enhanced performance and reduced emissions. One postdoc position is now open for candidates with expertise and experience in process modeling (preferably using
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your PhD in computer science or engineering, the physical sciences, or a related field within the last five years. Comprehensive programming proficiency, preferably in Python. Experience with machine
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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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Quantum Theme, focusing on Next-Generation Quantum Systems. The successful candidate will lead efforts to discover and design quantum emitters with desirable properties for quantum information science (QIS
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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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team that focuses on materials for classical microelectronic interfaces and quantum information science. The group actively interacts with the broader Argonne and UChicago community of scientists as
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The Multiphysics Computation Section within the Transportation and Power Systems Division at Argonne National Laboratory is seeking to hire a postdoctoral appointee. The successful candidate’s
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multidisciplinary team, the Postdoctoral Appointee will work at the intersection of AI/ML, climate science, and high-performance computing. The candidate will develop LLMs specifically designed to understand, process
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(predoctoral) or PhD (postdoctoral) in Materials Science, Chemistry, Physics, or related area is required. Coursework in computer science or data science is desirable. Familiarity with research data management