Assistant Researcher Position in Machine Learning and Climate

The UCLA Center for Climate Science is searching broadly for a talented Assistant Researcher scholar to work with Professor Alex Hall and his research group, contributing to research that utilizes machine learning methods to better understand local to global climate variability and change. The term would initially be for two years, but is renewable for at least one additional year, contingent on funding and satisfactory progress. The Assistant Researcher will have freedom to pursue projects of mutual benefit and will generally employ various explainable AI/ML techniques to address questions related to shifts in average climate conditions and the frequency of extreme weather events. Data sources include observations, global climate model output, and dynamically downscaled data at the regional scale across the United States. (The group has generated an unprecedented trove of multi-model regional high resolution future climate change projections.) These methodologies will be utilized to enhance the transparency and interpretability of predictive models dealing with complex climate data. Possible research areas include detection and attribution of hydroclimate signals, enlargement of high resolution regional ensembles through AI-based downscaling, building frameworks for reducing uncertainty in climate model projections, isolating the role that different climate forcings (e.g. aerosols) exert on recent trends, and improving predictability of hydroclimate change on annual to decadal timescales.