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for holotomography and to perform dynamic experiments using the Projection X-ray Microscope (PXM) instrument for studying microelectronics. As part of a collaborative team, the successful candidate will participate in
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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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The Applied Materials Division (AMD) in the Emergent Materials and Process Group at Argonne National Laboratory in looking for a Post-doctoral Appointee -- Pyrometallurgy. The candidate will perform
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to energy conversion. The research involves exploring the excited-state structural dynamics and mechanisms of photoinduced energy and charge transfer across a wide spectrum of systems, including small
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information Ability to model Argonne’s Core Values: Impact, Safety, Respect, Integrity, and Teamwork Desired skills, knowledge and abilities: Experience with large-scale molecular dynamics (MD) simulations
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Investigate how dynamic stimuli manipulate catalyst electronic properties, and how these stimuli can manipulate catalytic elementary steps and reaction outcomes Perform detailed in situ / operando studies
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this work we investigate how molecular materials coupled to solid-phase scaffolds may influence molecular motion, photoinduced kinetics, charge dynamics, and assembly durability. The work will target
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methods and software for the analysis and calibration using very large data sets resulting from dynamical simulations on high-performance computing resources. Application areas include : 1. Epidemiology, 2
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dynamics (CFD) to develop and optimize new processes and equipment designs using high-performance computing Analyze data, prepare manuscripts for submission to peer-reviewed publications, prepare technical
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contributions in: Building novel generative models for predicting genome-scale evolutionary patterns using GenSLMs Developing scalable models that can, when integrated with high throughput molecular dynamics