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predictive MD simulations capable of resolving atomic-scale LCI mechanisms with near-DFT accuracy Investigate how silicon suppresses LCI, including its effects on grain boundary site competition and the
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development of a Density Functional Theory (DFT)-accurate machine-learned interatomic potential (MLIP) for the multi-component steel system of interest. Ultimately, this simulation-driven framework will allow
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for three consecutive periods (2014-2018 and 2018-2022 and 2023-2026). ICN2 comprises 20 Research Groups, 7 Technical Development and Support Units and Facilities, and 2 Research Platforms, covering different
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; previous experience as local contact at synchrotron XAS beamlines; knowledge of advance characterization techniques like XANES simulation and ab initio calculations (e.g. DFT). Good time management skills
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, please contact Duy Le at [email protected]. Responsibilities: The Postdoctoral Associate’s Responsibilities include but are not limited to: Performing computational modeling using DFT, GC-DFT, MD (AIMD
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semiconductors, including conjugated polymers. • Perform molecular dynamics simulations to investigate structural organization and molecular connectivity. • Carry out electronic-structure calculations
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and validate its accuracy against previous benchmarks for small molecules like PtH. This approach is general and can be directly combined with EOM-CC embedded in point charges, or in periodic DFT
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and validate its accuracy against previous benchmarks for small molecules like PtH. This approach is general and can be directly combined with EOM-CC embedded in point charges, or in periodic DFT
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Postdoctoral Research Associate- AI/ML Accelerated Theory Modeling & Simulation for Microelectronics
-approaches that allow integration of different theory, simulation, and experimental protocols. The research is designed to provide opportunities for development of your experience and scientific vision