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We are seeking a Postdoctoral Appointee to work in the Mathematics and Computer Science (MCS) Division of the Computing, Environment, and Life Sciences directorate (CELS) of Argonne National
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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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skills and qualifications: A recent PhD (completed within the last 5 years) in computer science, electrical engineering, or a related field. Strong background in network interconnect design and
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is typically achieved through a formal education in chemical engineering, chemistry, materials science, nuclear engineering, mechanical engineering, or related field at the PhD degree level with zero
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to develop, synthesize, characterize and electrochemically evaluate next generation cathode materials for lithium-ion and sodium-ion batteries. Position Requirements Recent or soon-to-be-completed PhD
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, modeling and analysis, integrating diverse data sets to identify global risks affecting sourcing strategies. In this role you will: Conduct and contribute to research and model development to enhance
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-aware multi-modal deep learning (DL) methods. At Argonne, we are developing physics-aware DL models for scientific data analysis, autonomous experiments and instrument tuning. By incorporating prior
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in high-voltage battery systems through a fundamental understanding of interfacial mechanisms. Position Requirements Recent or soon-to-be-completed PhD (within the last 0-5 years) in Organic Chemistry
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-be-completed PhD (typically completed within the last 0-5 years) in chemistry, chemical engineering, material science, or related fields. Demonstrated knowledge in materials synthesis and
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candidate will work on cutting-edge research integrating genome-scale language models (GenSLMs) with deep mutational scanning data, and experimental virology to predict viral evolution and identify emerging