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computational research in accelerator science and technology. The focus is on developing and applying machine learning (ML) methods for accelerator operations and beam-dynamics optimization in advanced
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in materials for electrochemistry. While the focus in on computational expertise, this position will involve some experimental work in adapting workflows for automation and artificial intelligence
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analysis Interdisciplinary Collaboration - Experience working in cross functional teams including molecular biologists, chemists, radiation experts and computational biologists Core Values - Ability to model
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on understanding novel and emergent behavior in nanoscale magnetic heterostructures, particularly in confined 2D van der Waals magnets and related devices. The goal of the program is to study and control magnetic
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of projects simultaneously. Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork. This position requires an on-site presence at the Argonne campus in Lemont
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contribute to open-source code repositories and documentation. Position Requirements Required skills, knowledge and qualifications: PhD in physical oceanography, coastal engineering, computational science
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Extensive knowledge of Microsoft Excel and good computer programming skills Knowledge of techno-economic analysis and life cycle analysis Experience working with Argonne’s EverBatt model, GREET model, and
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Python and either PyTorch or TensorFlow is required Experience using High-Performance Computers (HPCs) is preferred Ability to model Argonne’s Core Values: Impact, Safety, Respect, Integrity, and Teamwork
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facilities and instrumentation, publish in high-impact venues, and collaborate closely with scientists across CNM, Argonne, and external partners. Key Responsibilities Design, synthesize, and rigorously
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(MSD), and Quantum Information Science (QIS) programs Disseminate results through high-impact publications and presentations at internal and external meetings Position Requirements Position Requirements