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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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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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physics (HEP) and nuclear physics (NP) experiments. The successful candidate will be a key member of a multidisciplinary co-design team integrating materials science, computing, and device engineering to
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The Applied Materials Division (AMD) at Argonne National Laboratory is looking to hire a Postdoctoral Appointee – Materials Science. The Applied Materials Division conducts applied research
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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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, materials synthesis, and separation processes. Position Requirements Recent or soon-to-be-completed PhD (typically within the last 0–5 years) in chemistry, geochemistry, chemical engineering, physics
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. The candidate is expected to lead an effort to prepare generalized ML techniques for data quality monitoring for tasks across multiple HEP experiments. Experiments with Argonne involvement include, but are not
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PhD (within the last 0-5 years) in field of physics, chemistry, materials science, electrical engineering, or a related field Demonstrated expertise in electronic structure theory Experience with large
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experiments and corresponding data analysis. Following the successful demonstration of the technique, the candidate will collaborate with team members from material science to apply these methods to scientific
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at technical conferences. Position Requirements Recent or soon-to-be-completed PhD (typically completed within the last 0-5 years) in mechanical engineering, materials science, civil engineering, computer science