Scientist in Precipitation Remote Sensing


Starting Salary: Commensurate with experience

Closing Date: Open until filled


The Cooperative Institute for Satellite Earth System Studies (CISESS) at the University of Maryland, College Park, is actively seeking candidates to fill a position in satellite precipitation remote sensing. The successful candidate will join a dynamic team of scientists from CISESS and the National Oceanic and Atmospheric Administration (NOAA) with the primary goal of developing, enhancing, and expanding an operational global snowfall rate (SFR) product at NOAA. This product’s algorithm incorporates both 1DVAR-based retrieval and machine learning (ML) for enhancement. Currently, the SFR product is retrieved using a constellation of passive microwave sensors. Future expansions will include other measurement types and platforms. In close collaboration with fellow team members, the selected scientist will be responsible for performing some or all of the following duties:

  • Improve the 1DVAR forward radiative transfer model, including ice microphysics.
  • Enhance the SFR algorithm for challenging retrievals, such as orographic snowfall, using both physical and ML modeling techniques.
  • Extend the SFR algorithm to new satellites and sensors.
  • Calibrate and validate the SFR product against ground-based and space-borne radar estimates as well as ground observations.
  • Engage with and provide support to product users.
  • Publish research results in scientific journals and present findings at conferences and workshops.


  • A PhD degree in remote sensing, atmospheric sciences, or a related field
  • Or a MS degree in one of the above disciplines and at least 3 years of experience
  • Intermediate to in-depth knowledge of radiative transfer
  • Experience with ML and passive microwave radiative transfer modeling is highly desired
  • Excellent programming skills in one or more of the following scientific languages: C/C++, Fortran, Python, Matlab, and IDL; as well as proficiency in Linux scripting
  • Strong verbal and written communication skills
  • Ability to work both independently and collaboratively with the SFR team

This position can be filled at different levels including postdoctoral associate, depending on the applicant’s qualifications.  

To Apply: Interested candidates should send a CV with a list of at least 3 professional references and a cover letter explaining how your qualifications meet the posted requirements to Yongzhen Fan <>.