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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
modeling of large-scale dynamics in networks. This role involves creating large scale models of dynamic phenomena in electrical power networks and quantifying the risk of rare events to mitigate
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conventional and alternative energy sources, for enhanced performance and reduced emissions. One postdoc position is now open for candidates with expertise and experience in process modeling (preferably using
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is required. Collaborative skills, including the ability to work well with other divisions, laboratories, and universities. Ability to demonstrate strong written and oral communication skills. Ability
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. Hands-on experience working at beamlines at synchrotron facilities. Strong communication skills for working in a multidisciplinary team environment. Ability to synthesize research findings into work
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) year, with the possibility of extension for up to three (3) years, depending on funding and performance. Interested applicants should be prepared to arrange for three letters of reference to be provided
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. Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork. The candidate is expected to think and work independently as well as in a large team to conduct research in a
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The Materials Science Division at Argonne National Laboratory is hiring a postdoctoral appointee for investigating ion transport as a function of material structure and extent of hydration in
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quantum mechanical calculations (e.g., first principles density functional theory (DFT)) to identify the structures and to understand the complex mechanisms of molecular reactions occurring at the surface
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of the above areas will be considered. One of our open positions is to work with Andrew Hearin on forward modeling galaxy SEDs and the galaxy--halo connection with applications to DESI, LSST, and CMB cross
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postdoctoral appointee will use a combination of synchrotron X-ray surface scattering and imaging approaches. The work also involves the interpretation of experimental data and the presentation of results