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The Chemical Sciences and Engineering Division at Argonne National Laboratory welcomes applications for a Postdoctoral Appointee to join our Polymer Upcycling Team. In this role, you will contribute
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and engineers across Argonne, including the Materials Engineering Research Facilities (MERF) and the Argonne MXene Innovations (AMI) program, while collaborating with industrial and academic partners
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PhD (within the last 0-5 years) in field of materials science, chemistry, chemical engineering, computer science, or a related field Experience operating and troubleshooting laboratory automation
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) at Argonne National Laboratory to advance learning-enabled imaging methods. This position offers a unique opportunity for candidates with backgrounds in electrical engineering, computer science, applied
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of physical sciences, or in math, computer science, and electric engineering who have an interest in accelerator physics will also be considered. Strong programming skills. Proficiency in the Python programming
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cheminformatics or polymer informatics, molecular representations, descriptor engineering, RDKit, characterization-informed modeling, multimodal data fusion, interpretable machine learning, NLP, text mining
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together computer scientists, AI researchers, domain scientists, software engineers, and high-performance computing experts. You will help design and implement new methods for multimodal federated learning
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(within the last 0-5 years) in field experimental physics, engineering, or a closely related field Excellent written and verbal communication skills Demonstrated ability to work effectively in a
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well as in industry and at other national laboratories. Position Requirements Recent or soon-to-be-completed PhD (typically completed within the last 0-5 years)in Engineering or similar program. At least 2
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backgrounds such as engineering, computer science, statistics, and economics. Familiarity with energy technologies and associated supply chain risk and challenges. Familiarity with the application of statistics