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. Responsibilities include working with digital signal processing, advanced filtering techniques, dynamic feature extraction, time-domain and frequency-domain analysis, signal fusion and machine learning to enhance
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assessment models, and statistical modeling in both frequentist and Bayesian frameworks • A solid track record of publications Appointment Type Restricted Salary Information Commensuate with experience Review
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experience in developing models to analyze temporal data. Prior experience in utilizing Bayesian modeling in related applications. Required Application Materials: CV Contact information for reference letters
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references. If you advance to the final stage of the application process, references will be contacted via automated email, which may be filtered into spam or junk folders. We recommend informing your
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the surrogate forward models with a Bayesian inverse modeling framework to achieve real-time or near-real-time uncertainty quantification, such that we can efficiently resolve the uncertainties rising from rock
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, Uncertainty quantification, Approximation Theory, Applied Probability and Bayesian statistics, Optimal Control and Dynamic Programming. Appointment, salary, and benefits. The appointment period is two years
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Expertise in quantitative modeling, computational and/or Bayesian methods Expertise using at least one programming languages in the analysis of scientific data such as R, Python, Matlab, or Julia. Expertise
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scenarios; building network models in one or more platforms (e.g., loop analysis/qpress; fuzzy cognitive maps/Mental Modeler; Bayesian belief networks; etc.); and interpreting, communicating to broad