In Meso/Convective Scale Data Assimilation and Ensemble Prediction
The School of Meteorology of University of Oklahoma invites applicants for post-doctoral positions in the area of Meso/convective scale (e.g., continental Mesoscale Convective Systems, supercell, hurricanes, etc.) data assimilation and ensemble prediction. Successful candidates will work with the Multiscale data Assimilation and Predictability (MAP) Laboratory, one of the leading, vibrant and productive labs conducting active research and development in data assimilation and ensemble prediction for various scales and atmospheric phenomena. Successful candidates will conduct research to advance the assimilation of radar, satellite and other convective and meso-scale observations using advanced ensemble-variational hybrid data assimilation method developed based on the US National Weather Service operational data assimilation system GSI.
• Education and Experience:
Ph.D. in Atmospheric Science, Meteorology, Engineering, Computer Sciences, Physics, Mathematics or related disciplines
Experience in numerical modeling
• Skills and Proficiencies:
Demonstrated ability to work independently and collaboratively
Excellent written and oral communication skills
Fortran 90/95 programming experience in UNIX/LINUX environment
Familiarity with scripting and plotting languages
The successful candidates will work inside the National Weather Center where School of Meteorology resides. National Weather Center houses the University’s academic and research programs in meteorology, state organizations, and the U.S. National Oceanic and Atmospheric Administration (NOAA)’s Norman-based weather research and operational programs. Such academic and working environment will provide unique opportunities for the candidates to further build and advance their careers. Salary will be competitive based on experience and qualification. University of Oklahoma offers competitive benefits. Positions are open now until filled and full consideration will be given to applications received by January 31 2018.
To apply for the positions, please submit electronic applications, including a letter of research interest and experience, CV, and three names of references including their contact information to Prof. Xuguang Wang, at, firstname.lastname@example.org.