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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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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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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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ability to work effectively in a team environment with people of diverse backgrounds. Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork. Job Family Postdoctoral Job
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Flexibility to engage across multiple projects, research topics, and applications Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork Ability to maintain a full-time, on
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communication skills Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork Preferred Qualifications Familiarity with synchrotron-based X-ray techniques and electron microscopy
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effectively in an interdisciplinary team. Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork. Interpersonal skills, oral and written communication skills, and ability
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rules. Ability to work with large volumes of hazardous chemicals. Flexibility to change projects and work on a variety of projects simultaneously Ability to model Argonne’s core values of impact, safety