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PhD (typically completed within the last 0-5 years) in pyrometallurgy, chemistry, materials science, chemical engineering, or related scientific background with 0-3 years’ experience. Experience in
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relevant field at the PhD level with zero to five years of employment experience. Experience with deep learning frameworks (PyTorch, TensorFlow, JAX). Strong background in computational image processing and
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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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, 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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is supported by a DOE-funded research program on ultrafast science involving Argonne National Laboratory, University of Washington, and MIT. The goal of this research program is to understand and
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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
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of impact, safety, respect, integrity, and teamwork. This level of knowledge is typically achieved through a formal education in materials science, physics or related discipline at the PhD level or
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The Hydrogen and Fuel Cell Materials Group in Argonne National Laboratory’s Chemical Sciences and Engineering Division is seeking to hire a Postdoctoral Appointee to participate in a project that
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The X-ray Imaging Group (IMG) of the Advanced Photon Source (APS) is seeking a postdoctoral researcher with expertise in computational science and image processing to develop innovative methods
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The Environmental Science Division at the Argonne National Laboratory is seeking a postdoctoral scholar to conduct model simulations with high-resolution global and regional climate models