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models Disseminate research through publications, presentations, and open-source contribution Position Requirements Recent or soon-to-be-completed PhD (within the last 0-5 years) in Materials Science, Data
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to develop innovative technologies to improve the efficiency of resource utilization; to minimize our dependence on imported materials; and to enhance our national security. This position is broadly focused
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employer, and in accordance with our core values of impact, safety, respect, integrity and teamwork, Argonne National Laboratory is committed to a safe and welcoming workplace that fosters collaborative
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the essential functions of this position successful applicants must provide proof of U.S. citizenship and must be able to obtain and maintain a security clearance, which is required to comply with federal
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core values of impact, safety, respect, integrity and teamwork, Argonne National Laboratory is committed to a safe and welcoming workplace that fosters collaborative scientific discovery and innovation
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, experience in scaleup is a plus. Position Requirements Recent or soon-to-be-completed PhD (typically completed within the last 0-5 years) in chemistry and/or closely related discipline. Expertise in the study
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candidate would be a PhD in geophysical sciences, computer science, or machine learning with experience in developing and verifying deep learning-based models for large dynamical systems (e.g. weather
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of multi-omic data Programming Proficiency: Strong knowledge of Python, C/C++, Julia, and other relevant programming languages Ability to model Argonne's core values of impact, safety, respect, integrity
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
Requirements Required skills, abilities, and knowledge: Recent or soon-to-be completed PhD (within the last 0-5 years) by the start of the appointment in computer science, electrical engineering, applied
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, safety, respect, integrity, and teamwork Preferred Skills Hands-on experience with GEANT4-based simulations Experience with detector characterization and validation Familiarity with HEP/NP data processing