145 parallel-computing-numerical-methods Postdoctoral research jobs at Princeton University
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. Some experience with first-principle methods (FP/DFT) and/or other forms of electronic and magnetic structure theory and calculations is also expected. The successful candidate will have a strong
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to ion beams with well-controlled energies and incident angles for benchmarking and validation of theoretical calculations and computational physics and chemistry modeling of important surface processes
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/or energy *Strong methodological and quantitative skills, such as survey and sampling design and data analysis (in R or Python), meta-analysis and/or document/text analysis, or computational modeling
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spectroscopic and imaging techniques for UHV surface science experiments and methods. Additional expertise in plasma, plasma-materials interactions, and/or ALE is of significant value. Experience with the design
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: 275950536 Position: Postdoctoral Research Associate in Microfluidics, Nanofabrication, and Nanophotonics Description: The Department of Electrical and Computer Engineering has opening for postdoctoral
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-to-Decadal Variability & Predictability Division, Technical Services and Modeling Systems Division. The selected candidate will have access to state-of-the-art numerical models and high-performance computing
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superconductors. The successful candidate must have substantial experience in state-of-the-art ARPES and/or low temperature STM/STS techniques. Some experience with first-principle methods (FP/DFT) and/or other
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interested in computational materials design and discovery. The successful candidate will develop new, openly accessible datasets and machine learning models for modeling redox-active solid-state materials
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, such as survey and sampling design and data analysis (in R or Python), meta-analysis and/or document/text analysis, or computational modeling *An interest in mixed-methods approaches, including also
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include: a Ph.D. in Neuroscience, Psychology, Cognitive Science, Computer Science, Engineering, or other related field, and strong experience with computational models, programming, and quantitative methods