|Date Posted||June 7, 2020|
We are looking for a Numerical Weather Prediction (NWP) Scientist to join SAIC supporting the Air Force weather community and the TADS contract. The successful candidate will provide expertise to support and enhance NWP capabilities derived from a variety of models including, but not limited to, WRF, GFS, and the UK Met Office Model. Key tasks involve applying data assimilation techniques, developing new applications exploiting NWP data, verifying model output against observational data, working with data scientists to develop and implement machine learning and artificial intelligence methods for weather forecasting, and developing new techniques to analyze and predict the global cloud field, while working in an AWS high-performance computing (HPC) environment. The NWP Scientist will create and enhance innovative solutions that satisfy Air Force operational weather analysis and forecasting needs while working on an Agile team with scientists, data scientists, and software development staff. Responsibilities:
• Develop NWP tools and techniques supporting the Air Force weather forecasting community.
• Support and develop operational NWP applications in an AWS HPC cloud-based environment.
• Validate NWP model skill and devise methods for continual improvement of the forecast system.
• Develop new NWP tools and techniques to analyze and predict the global cloud field.
• Perform applied research into the use of data science techniques to improve atmospheric cloud forecasts to include continuous monitoring and alerting or scientific software systems
• Work with data scientist to identify and implement machine learning and artificial intelligence methods focused on weather forecasting for military applications.
• B.S. in Meteorology or equivalent with a specialization in Numerical Weather Prediction
• 3 years experience working with operational NWP models.
• Experience with WRF, GFS, MM5, or other NWP systems.
• Experience with Python and FORTRAN.
• Experience developing and verifying NWP algorithms and software systems.
• Knowledge of meteorological data formats like METAR, GriB, NetCDF, etc. Desired Qualifications and Experience:
• Ph.D. in Meteorology.
• Experience with variational data assimilation.
• Experience developing atmospheric cloud modeling applications
• Experience leveraging machine learning and/or artificial intelligence methods for environmental science.
• Experience with Air Force weather forecasting.
• Familiarity with the Air Force CDFS-II system
• Experience with HPC in a cloud-based environment.
#AirForce #Army #SAIC
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