Climate

& Data Science

Department of Atmospheric Science, Colorado State University

WE ARE HIRING POSTDOCS!

[more details / apply here]


The Barnes Research Group at Colorado State University’s Dept. of Atmospheric Science is looking to hire two postdoc positions in the area of artificial intelligence (AI) for climate science! Specifically, the individual(s) will design and implement novel AI approaches for the prediction of earth system phenomena under past, present, and future climates. Research topics will include predicting extreme events on subseasonal-to-decadal time horizons, training, implementing and evaluating modern AI-weather/climate emulators, developing transfer learning approaches for climate models and observations, and using high-performance computing including GPU computing. A focus of the Barnes Research Group is the use of explainable/interpretable AI, and this position will work to further advance methods in this area. 

The Barnes Research Group is a leader in the exploration of novel uses of AI for Earth system research and will support the successful candidate in contributing to this expanding field. This is a high-impact position at the forefront of data science for Earth system research and will provide exceptional opportunities for a motivated researcher to push the boundaries of AI for climate science applications. The postdoctoral position(s) will interact with and support graduate students and early career researchers, especially from the Barnes Research Group, but also other research groups across the Atmospheric Science Department and with collaborators at institutions across the country.

The Department of Atmospheric Science at Colorado State University is a large academic and research department in the Walter Scott, Jr. College of Engineering. The Barnes Research Group is comprised of highly motivated researchers passionate about climate variability and change and the data analysis tools used to understand it. Areas of active research include earth system predictability, subseasonal-to-seasonal (S2S) prediction, climate dynamics, climate change and sustainability, impacts of climate intervention, and explainable/interpretable AI for earth system research.

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