The University of Maryland/CISESS has a position open at the Post-Doctoral/Assistant/Associate research scientist rank to support the Cross-track Infrared Sounder (CrIS) Sensor Data Record (SDR) Algorithm Calibration and Validation Science Team (ACVST) led by NOAA/NESDIS/STAR.
As a member of the CrIS SDR ACVST, the incumbent will develop tools and perform analysis for the calibration and validation of the CrIS instrument. The CrIS sensor is a Fourier Transform Spectrometer currently flying on-board the Suomi National Polar-orbiting Partnership (SNPP), NOAA-20, and recently launched NOAA-21 spacecrafts, and planned for the JPSS-3 and -4 satellites. The CrIS SDR ACVST has the responsibility of the science algorithms for transforming the CrIS raw data records (RDR) into high quality geolocated and calibrated radiance product called the SDR. This position involves the participation in pre-launch and post-launch calibration and validation activities of CrIS observations.
Primary Responsibilities:
- Develop, test and evaluate the different components of the operational CrIS SDR calibration algorithm.
- Develop, improve and implement methodologies for the radiometric, spectral, and geometric calibration and validation of CrIS observations.
- Investigate, monitor and derive solutions for potential anomalies related to CrIS instruments.
- Support CrIS pre-launch and post-launch activities.
- Publishing research results in peer-reviewed journals.
- Participate in technical meetings and conferences including presentations.
Desired Qualifications:
Holding some of the following qualifications is highly desired:
- A Master’s degree (Ph.D. preferred) in Atmospheric Sciences, Physics, Aerospace Engineering, Computer Science, Remote Sensing, Electrical Engineering, Signal Processing or a related physical science.
- Preferred experience in some of the following programming languages: Python, Matlab, IDL, C/C++, Fortran 90/95, Shell scripting.
- Experience in Optics, such as interferometry.
- Experience with Fourier Transform Spectrometers.
- Experience with Hyperspectral Infrared Observations.
- Experience with Data Science techniques such as Machine Learning.
- Broad knowledge of the physical basis of remote sensing.
- Experience with analyzing satellite data. Knowledge and experience with atmospheric sounding products are a plus.
- Familiarity with radiative transfer models, including the LBLRTM and CRTM models.
- Familiarity with GitHub and GitLab.
- Experience working in a Linux environment.
- Excellent oral, written and interpersonal communication skills.
- Ability to work with others as a research team.
- Ability to work in a culturally diverse environment.
To Apply: Interested candidates should send a CV with at least 3 professional references and a cover letter explaining how your qualifications meet the posted requirements to pbeierle@umd.edu
