Theoretical and Applied Data Assimilation Scientist
The Cooperative Institute for Research in the Atmosphere (CIRA) at Colorado State University (CSU) is a multi-million dollar research organization located on CSU’s Foothills Campus in Fort Collins, Colorado. CIRA is a cooperative institute (CI) that is also a research department within CSU’s College of Engineering, in partnership with the Department of Atmospheric Science. Its vision is to conduct interdisciplinary research in the atmospheric sciences by entraining skills beyond the meteorological disciplines, exploiting advances in engineering and computer science, facilitating transitional activity between pure and applied research, leveraging both national and international resources and partnerships, and assisting the National Oceanic and Atmospheric Administration (NOAA), CSU, the State of Colorado, and the Nation through the application of our research to areas of societal benefit. Expanding on this Vision, our Mission is to serve as a nexus for multi-disciplinary cooperation among CI and NOAA research scientists, University faculty, staff and students in the context of NOAA-specified research theme areas in satellite applications for weather/climate forecasting. Important bridging elements of the CI include the communication of research findings to the international scientific community, transition of applications and capabilities to NOAA operational users, education and training programs for operational user proficiency, outreach programs to K-12 education and the general public for environmental literacy, and understanding and quantifying the societal impacts of NOAA research.
The Cooperative Institute for Research in the Atmosphere (CIRA) at Colorado State University seeks to fill a postdoctoral fellowship as part of a National Science Foundation (NSF) award to be located at CIRA in Fort Collins, Colorado. This fellowship may last up to 3 years contingent upon NSF funding availability. The individual in this position will be part of the data assimilation group and will work on developing links between non-Gaussian distributions and different atmospheric scale dynamics, converting the hybrid version of WRF-GSI to have a non-Gaussian component, as well as developing and implementing different probability density functions detection algorithms.
Required Job Qualifications
- PhD by the start date in Physics, Mathematics, Statistics, Remote Sensing, Meteorology, or related physical science field plus 1 year of experience working with data assimilation systems;
- higher education in fundamental physics and/or mathematics;
- experience programming in Fortran90 or higher and Linux scripting;
- ability to travel to domestic and international conferences.
Preferred Job Qualifications
- experience working with variational data assimilation;
- knowledge of WRF-GSI;
- knowledge of Bayesian Theory;
- knowledge of the mathematical field of Numerical Analysis, i.e. preconditioning, numerical linear algebra, NSDE etc;
- knowledge of mesoscale and/or synoptic meteorology;
- stochastical modeling experience;
- machine learning experience;
- proficiency in MATLAB or equivalent analysis and display software.
Reflecting departmental and institutional values, candidates are expected to have the ability to advance the Department’s commitment to diversity and inclusion.
Job Duty Category Non-Gaussian Dynamical Linkages Duty/Responsibility
- develop mathematical and/or stochastical model to link probability density functions to different atmospheric dynamics;
- implement and test the new model with toy problems;
- implement and test the new model with the WRF test cases.