123 parallel-computing-numerical-methods Postdoctoral positions at Princeton University
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The Joseph Research Group at Princeton University is searching for postdoctoral candidates interested in computer simulation studies of intracellular spatiotemporal organization, biomolecular self
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gravitational-wave astrophysics. Research topics include analysis and astrophysical interpretation of LIGO-Virgo-KAGRA data, forecasting and statistical methods development for next-generation gravitational-wave
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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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, 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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for benchmarking and validation of theoretical calculations and computational physics and chemistry modeling of important surface processes occurring at plasma-material interfaces in fusion plasma edges, i.e
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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
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. Individuals with expertise in relevant modeling methods are encouraged to apply, including but not limited to integrated assessment modeling, energy system modeling, climate and air quality modeling, and agent
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modeling methods and tools. Applicants should have strong, demonstrated research ability, and excellent English written and spoken communication skills. Preference will be given to applicants with
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research thrusts (or both): 1.Applied operations research: scholars will develop and implement novel methods to improve the computational performance and resolution of large-scale optimization models