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infrastructure, autonomous lab systems, and nanomaterials science. This position emphasizes developing and applying advanced data-driven methodologies to accelerate discovery across materials design, experimental
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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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techniques to solve pressing challenges in energy storage. The successful candidate will work in the Data Science and Learning division of the Computing, Environment, and Life Sciences directorate of Argonne
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, Astrophysics, Physics, Cosmology, or a related quantitative field (e.g., Applied Mathematics, Computer Science, Statistics, Data Science) Demonstrated research experience in observational cosmology or wide-field
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-completed PhD (within the last 0–5 years) with strong background in physical chemistry, photophysics, photochemistry, and polariton chemistry Hands-on experience in thin-film deposition, and spectroscopic
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The Data Science and Learning Division (DSL) at Argonne National Laboratory is seeking a postdoctoral researcher to conduct cutting edge molecular and microbiology work to enhance non-proliferation
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. Position Requirements Recent or soon-to-be-completed PhD (typically completed within the last 0-5 years) in mechanical engineering, materials science, civil engineering, structural engineering, or a closely
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, supply chain risk analysis, and data-driven modeling (including AI/ML where appropriate) to help inform decision-making for energy deployment and national competitiveness. In this role you will : Conduct
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superconducting RF (SRF) technology. Since then, a transformative SRF approach using Nb₃Sn has emerged, offering performance comparable to niobium while enabling operation at higher temperatures—potentially
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or soon-to-be-completed PhD (typically completed within the last 0-5 years) in physics, chemistry, or materials science with 0 to 2 years of experience, or the equivalent experience through practical