University of Oklahoma Norman Campus: Atmospheric and Geographic Sciences: School of MeteorologyDescription:The Applied Climate Dynamics research group led by Dr. Jason Furtado in the School of Meteorology at the University of Oklahoma is looking to hire a Postdoctoral Research Fellow to develop a subseasonal prediction tool for extreme cold air outbreaks (CAOs) across Eastern Europe. The successful candidate will be responsible for:
- Defining and creating a database of past (since 1979) CAOs across Eastern Europe.
Identifying important and skillful precursor patterns in the atmosphere, ocean, and land-surface leading up to these extreme CAO events.Building and training a subseasonal prediction tool to be used for probabilistic predictions of these events from Weeks 1-5 for operational partners.Evaluating the historical and real-time prediction performance of this prediction tool against existing operational subseasonal forecast models.Interested candidates should have experience with working with large datasets and numerical model output, synoptic and subseasonal forecasting, and large-scale patterns of variability. The successful candidate will join a new research center at the University of Oklahoma focused on extreme weather resiliency. The postdoctoral research fellow will be supervised by Dr. Jason Furtado and will collaborate with others in that center and at the University of Oklahoma on tasks and related research projects.
The successful candidate will work in the National Weather Center in Norman, OK where the School of Meteorology and several state and federal weather agencies reside. The National Weather Center fosters a uniquely collaborative work environment with federal, state, and academic units, providing valuable networking opportunities for career development.
Salary will be competitive based on rates from a recent survey of postdoctoral fellowships in the United States and adjusted to the cost of living in Oklahoma. Full consideration will be given to applications received by 23 November 2026, but applications may be submitted until the position is closed. Candidates in the final stages of completing their Ph. D. are also encouraged to apply. The term of appointment will be for one year, renewable for a second year subject to satisfactory performance.
Qualifications:Required Qualifications- Ph. D. in Meteorology, Atmospheric Science, Computer Science, Physics, or related disciplines
- Experience with working with large datasets, data analysis, and machine learning
- Demonstrated proficiency in Python
Desired Skills and Qualifications- Excellent written and oral communication skills
- Knowledge of subseasonal-to-seasonal prediction and operational subseasonal models
- Experience working with operational end users in a research environment
