The CASCADE project at Lawrence Berkeley National Laboratory (LBNL) is looking for a postdoctoral researcher to develop and apply statistical methods to the study of extreme weather events in a changing climate.
The postdoc will work with statisticians at the University of California, Berkeley and climate scientists from LBNL as part of the interdisciplinary Calibrated and Systematic Characterization, Attribution, and Detection of Extremes (CASCADE) project.
We seek a statistician with expertise and interest in statistical methods relevant for climate/atmospheric/
The goal of this position is to develop and use statistical methods to detect and characterize extremes with an emphasis on quantifying the changing risk of these phenomena from anthropogenic influences. The position entails using a combination of statistical methods such as spatial and spatio-temporal statistics, extreme value analysis, the bootstrap, and Bayesian methods to estimate the probabilities of climate events under different scenarios. A key focus will be to quantify the uncertainty in the probabilities in light of a wide variety of sources of uncertainty, including sampling uncertainty and model error. The researcher will evaluate, extend and implement existing methods and develop new statistical frameworks and methods.
The researcher will work with climate scientists to apply the methods to cutting-edge datasets of observations and model output, including models and data products developed and run at LBNL.
More details and application information available at https://lbl.taleo.net/
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