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these areas. Ability to work independently on a day-to-day basis. Demonstrated interpersonal, oral, and written communication. Ability to model Argonne’s Core Values: Impact, Safety, Respect, Integrity, and
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agencies and other national laboratories. The candidate will develop power systems and electricity market modeling, and analytics tools that support energy, economic, and financial analyses of power grid
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/ML model development to design and discover redox-active materials with tunable properties (structure, charge state, etc.) Discovery of novel materials for energy storage and conversion and their
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material property database for composites. The candidate will utilize the database to develop AI models for composite discovery. The candidate will work with a multidisciplinary team to set up finite element
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processes and develop models of material interactions and behavior in molten salt environments. Develop novel and improved methods for measurements of molten salt properties and standardizing procedures
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and teamwork capabilities, with a track record (or potential) in writing publications and presenting scientific results Ability to model Argonne’s core values of impact, safety, respect, integrity, and
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High-Energy Physics (HEP). We seek highly qualified candidates with interest and experience in ML algorithms including unsupervised techniques, time-series modeling, and clustering algorithms
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, distributions, and dynamics in metallic, oxide, and semiconducting systems. This project integrates high-throughput and in situ TEM experimentation with AI/ML-driven image analysis and computational modeling
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lead efforts to develop experimental techniques using conventional and coherent imaging in the ultrafast time domain, as well as a computational framework for modeling and reconstructing images
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experimentalists, modelers, and data scientists Position Requirements Recent or soon-to-be-completed PhD (within the last 0-5 years) in field of Materials Science, Chemical Engineering, Chemistry, or a related field