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.
Required Job Qualifications:
A Ph.D. in an earth science field (e.g., climate science, atmospheric science) or Ph.D. in a computer science/data science field with research experience in the earth sciences
Demonstrated experience applying machine learning techniques to earth system data
Demonstrated experience working with large earth system data sets
Demonstrated experience writing and publishing scientific results in leading journals
Strong oral and written communication skills
Publication record commensurate with experience
Ability to work both independently and collaboratively
Preferred Job Qualifications
Preferred Qualifications:
Research experience related to climate prediction on subseasonal-to-decadal timescales
Demonstrated research experience building novel machine learning architectures and applying them to earth system data
Familiarity and/or experience working with CMIP3/5/6 climate model output
Familiarity and/or experience working with state-of-the-art AI weather/climate emulators (e.g.,Pangu Weather, FourCastNet, FourCastNet-v2, GraphCast, ClimaX)
Questions & Applying:
For more information please contact Prof. Barnes at eabarnes@colostate.edu
Positions are available immediately, but the start date is flexible.
To find out more about the Barnes Research Group, visit: https://barnes.atmos.colostate.edu
To apply, please go to the open postdoc pool (it is a different link from the position description above): https://jobs.colostate.edu/postings/125988
explainable AI (XAI) for earth science
subseasonal-to-decadal predictability
climate intervention
climate change and sustainability
large-scale atmospheric dynamics
causal discovery