CIMMS Post-Doctoral Research Associate
Warn-On-Forecast Prediction Using Machine Learning
The Cooperative Institute for Mesoscale Meteorological Studies (CIMMS) at The University of Oklahoma seeks to fill a Post-Doctoral Research Associate position for its collaborative research as a Cooperative Institute with the National Oceanic and Atmospheric Administration (NOAA) Office of Oceanic and Atmospheric Research (OAR) National Severe Storms Laboratory (NSSL). The Post-Doctoral Research Associate will participate in NSSL’s Warn-on-Forecast (WoF) research program.
CIMMS in collaboration with NSSL is funded to develop and demonstrate a convection-allowing ensemble prediction system to improve warnings and forecasts of thunderstorm hazards. Increasing severe thunderstorm, flash flood, and tornado warning lead times is a key NOAA strategic mission goal designed to mitigate weather impacts on life, property, and the economy. Machine learning (ML) has proven an effective tool for postprocessing convection-allowing ensemble output to produce probabilistic forecasts of individual thunderstorm hazards. ML models have already been developed for the prototype WoF System (WoFS) that is run annually in real-time during the warm season. As a CIMMS Post-Doctoral Research Associate working with NSSL, you will continue the development of WoFS-based ML models and interpretability tools for predicting severe weather. While you will need to be primarily self-directed, you will work closely with other members of NSSL’s Warn-on-Forecast team.
The principal duties of this position are to:
1. Improve the existing WoFS-based ML prediction system, including implementation of additional ML and interpretability algorithms.
2. Facilitate the transfer of the WoFS-based ML prediction system into operations via collaborations with the National Weather Service and the NOAA Hazardous Weather Testbed.
3. Regularly present work at national conferences and publish in high-quality peer-reviewed journals.
The minimum qualifications for the position are:
1. A PhD in Meteorology or related area (or on target to complete PhD by December 2020)
2. United States citizenship or permanent residency
3. Experience analyzing output from convection allowing models
4. Experience with machine learning in meteorological applications
5. Proficiency with programming languages (preferably Python) and UNIX
6. Ability to work and communicate in a team environment
The beginning salary will be based on qualifications and experience with benefits provided through The University of Oklahoma (https://hr.ou.edu/Employees). The start date for the position is negotiable.
To apply for the position, please forward your CV, cover letter, and list of three references to:
University of Oklahoma CIMMS
120 David L. Boren Blvd., Suite 2100
Norman, OK 73072-7304
The University of Oklahoma is an equal opportunity/Affirmative Action employer.
To apply for this job email your details to CIMMSfirstname.lastname@example.org