139 parallel-computing-numerical-methods Postdoctoral research jobs at Princeton University
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Research Associates. DDSS supports technical and methodological innovation in quantitative and computational social science, addressing a diverse array of new data and analytic challenges, facilitating
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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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Minds initiative takes advantage of advances in AI to study natural and artificial minds in parallel, creating the opportunity to make discoveries about ourselves and to find new ways to understand and
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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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experience with both analytic methods and scientific computing. *CV, including complete list of publications. We are seeking to recruit from as diverse a pool of talent as possible, and endeavor to preserve
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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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Postdoctoral Research Associates in a parallel job posting. The Postdoctoral Research Associates will be appointed through the Center for Statistics and Machine Learning with the possibility for affiliation with
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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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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