Remote Sensing SAR Specialist and Developer (GS26100926)
gtsc talent solutions a gtsc companyCollege Park (MD)
Remote Sensing SAR Specialist and Developer (GS26100926)
Posted today
gtsc talent solutions a gtsc companyCollege Park (MD)
SENIORITY
Lead
About the role
Job Information:
GTSC and its Global Sciences and Technology (GST) business unit seeks a SAR specialist and developer to support NOAA/NESDIS/STAR. This position is located in College Park, MD.
Position Summary:
The successful candidate will work with a group of Synthetic Aperture Radar (SAR) scientists and software developers at the Satellite Oceanography and Climatology Division (SOCD) under the NOAA Center for Satellite Applications and Research (STAR). This position could be long-term depending on performance and Federal Government Funding.
Primary Duties:
The individual in this position will be responsible for the development and maintenance of science code for production of flood mapping datasets from multiple SAR sensors (e.g., Sentinel-1, RADARSAT Constellation Mission, RADARSAT-2, and NISAR). Development, implementation, and improvement of flood inundation detection algorithms, and evaluation of their performance. This is a scientific position that requires a strong understanding of physical science, mathematics, and scientific computing. Additional duties may include: Classification studies of river ice, i.e., detecting ice jams, tracking ice movement and breakup, and assessment of flooding risk. Utilizing SAR imagery to identify, outline, and characterize suspected oil slicks. Assisting with additional coastal, ocean, and cryosphere applications of SAR.Required
Education/Experience/Skills:
PhD or MS, with a minimum of 5 years of professional experience, in a quantitative field of research such as Remote Sensing, Oceanography, Physics, Mathematics, or Statistics. Knowledge of SAR remote sensing, satellite & oceanographic data, systems, and analyses. Proficiency with Python and IDL programming languages. Experience with application of machine learning algorithms using PyTorch or TensorFlow is desired, however, a working knowledge of machine learning techniques will suffice. Experience with data formats frequently used by the remote sensing community such as netCDF4, HDF5, GeoTIFF, Xarray, and Zarr. Experience with Linux operating systems and common tools. Proven list of deliverables (peer-reviewed publications, derived products, software packages, etc.). Willingness and ability to conduct independent research (problem definition, technical solution, coding, publication) while being a team player. Strong scientific analytical skills with detail-oriented working style.
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