Deep Learning and Coupled Human-Climate Postdoctoral Fellow

at  Colorado State University

DESCRIPTION OF WORK UNIT

Founded in 1870, Colorado State University is among the nation’s leading research universities and enrolls approximately 32,000 undergraduate, graduate, and professional students. Located an hour north of the Denver metro area, Fort Collins is a vibrant community of approximately 157,000 residents that offers the convenience of a small town with all the amenities of a large city. Fort Collins is situated on the Front Range of the Rocky Mountains with views of 14,000 foot peaks, and offers access to numerous cultural, recreational, and outdoor opportunities.
The Department of Atmospheric Science at Colorado State University is a large academic and research department in the Walter Scott, Jr. College of Engineering. We currently have 23 faculty members, eighty graduate students, over seventy full-time researchers and postdoctoral fellows, and an outstanding and dedicated support staff, that comprise one of the most research-active units at the university. The department conducts more than $14M in externally sponsored research each year and is nationally ranked near the top of its field.
The Barnes, Keys and Hurrell Research Groups are comprised of highly motivated researchers passionate about climate variability, climate and societal change, and the data analysis tools used to understand them. Areas of active research include questions around the impacts of various climate mitigation and intervention strategies, earth system predictability across timescales, Anthropocene dynamics and change, high-resolution regional climate modeling, climate dynamics, climate change and sustainability, and explainable/interpretable AI for earth system research.

POSITION SUMMARY

The postdoctoral scientist will work with the Barnes, Keys and Hurrell research teams to conduct independent and collaborative research related to the physical and societal impacts of various climate change and proposed climate intervention strategies by developing and applying hybrid deep-learning and coupled human-Earth system modeling frameworks to explore these questions. The position will help define the research and development direction of the research team in climate futures of the next 30 years, as well as participate in opportunities to apply earth system expertise to research efforts in other disciplines across and beyond the CSU campus. This is an exciting, high-impact position at the forefront of climate science and data science for coupled human-Earth system research and will provide exceptional opportunities for a motivated researcher to push the boundaries of current understanding.
The postdoctoral scientist will interact with and support graduate students and early career researchers, especially from the Barnes, Keys and Hurrell research groups, but also other research groups across the Atmospheric Science Department and Colorado State University. This position will report directly to Prof. Elizabeth Barnes and will be a part of a vibrant community of researchers within the Barnes, Keys and Hurrell groups, the Atmospheric Science Department, Colorado State University, and other funded collaborators.

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 both independently and collaboratively
• Demonstrated experience working with large and/or complex data sets
• Demonstrated experience writing and publishing scientific results in leading journals
• Strong oral and written communication skills.
• Publication record commensurate with experience.

PREFERRED JOB QUALIFICATIONS

• 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-v2, GraphCast, ClimaX, ACE)

• Serve as a prominent researcher within the Barnes/Keys/Hurrell groups by conducting substantive scientific research at the intersection of AI and climate science
• Explore, develop and utilize machine learning approaches for analyzing climate model output and observations to better understand and predict the changing Earth system
• Develop solutions to complex problems, understand the results and recommend research strategies
• Solve research questions by incorporating relevant new ideas, techniques and developments
• Interact with members of the research group(s) and relevant collaborators by supporting their researc