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Field
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project is to develop scalable and privacy-preserving Bayesian computational algorithms. The position is intended for two to three years, with an initial one-year appointment renewable contingent upon
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. Applicants with experience in Bayesian modeling, spatial statistics, mathematical modeling, data integration, uncertainty quantification and/or machine learning are encouraged to apply. The postdoc will also
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the frequency domain, photoelectron spectroscopy will offer insight into the dynamics of the resonance from a static perspective, while time-resolved photoelectron spectroscopy will track the autodetachment
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projects ranging from score-based generative models, energy-based models, Bayesian analysis of graph and network structured data, highly multivariate stochastic processes; with data applications ranging from
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mathematical information science approaches, such as scientific machine learning. Potential research topics include, but are not limited to: (1) Bayesian estimation of 3D velocity structure models using ocean
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spectroscopy will track the autodetachment to internal conversion and dissociative electron attachment products in real-time. Key responsibilities: To understand and convey material of a specialist or highly
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with Bayesian/ML methods is a plus Proactive, collaborative communicator with sound statistics, problem‑solving skills, and a commitment to research integrity and open, reproducible science We offer
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- identifying which measurements are most informative and guiding where, when and how to observe next. By combining Bayesian inference, probabilistic modeling, and machine learning, the project aims to make
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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 2 months ago
. The work will apply state-of-the-art three-dimensional atmospheric chemistry and circulation models, together with advanced statistical techniques (optimal Bayesian, Markov Chain-MonteCarlo, etc.) to solve
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, clustering analyses, propagating location and other uncertainties...) of mid-ocean ridge catalogs, using standard, Bayesian and machine learning techniques. ⁃ Implement methodologies that improve estimates