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The Computational Science Division (CPS) at Argonne National Laboratory (near Chicago, USA) is seeking a postdoctoral researcher to enable exascale atomistic simulations of ferroelectric devices
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modeling of crystals, dislocation dynamics, and defect analysis, linking atomic-scale simulations to macroscopic properties. Familiarity or interest in machine learning methods and computing frameworks
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all areas of experimental condensed matter physics will be considered, particular emphasis will be placed on the dynamical studies of 2D materials and their functionalities. This postdoctoral position
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Quantum Theme, focusing on Next-Generation Quantum Systems. The successful candidate will lead efforts to discover and design quantum emitters with desirable properties for quantum information science (QIS
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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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familiarity with DMS and DERMS functionalities and architectures; evaluate and enhance operational schemes under high DER penetration. Model microgrids in distribution networks including dynamic and steady
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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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-throughput workflows for data acquisition and analysis Contribute to on-the-fly data processing and integration with computational tools Collaborate with multidisciplinary teams in nanofabrication
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for quantum information science, but many open questions remain regarding how to control the morphology and crystallinity of these host materials for exemplary performace as hosts for optically addressable spin
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techniques in interfacial science; and mathematical techniques and computer programming for data analysis. Considerable skill in working interactively and productively in a multidisciplinary environment Good