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Strengthening NASA Air Quality Observations Low-Cost Sensor Data

Job in California, Moniteau County, Missouri, 65018, USA
Listing for: Sigma Earth
Full Time position
Listed on 2026-03-01
Job specializations:
  • Research/Development
    Data Scientist, Research Scientist
  • Engineering
    Research Scientist
Salary/Wage Range or Industry Benchmark: 60000 - 80000 USD Yearly USD 60000.00 80000.00 YEAR
Job Description & How to Apply Below
Position: Strengthening NASA Air Quality Observations with Low-Cost Sensor Data
Location: California

Description

NASA’s Ames Research Center is seeking a postdoctoral researcher to join the Trace Gas Measurement Group, with a focus on low-cost sensor technology and data fusion. The role involves hands‑on work with air quality sensors—building, calibrating, and deploying them—as well as analyzing data from NASA’s INSTEP sensor network. The goal is to improve sensor performance and enhance their integration with other NASA air quality data sources.

The researcher will contribute to fusing sensor outputs with data from remote sensing platforms such as Pandora, AERONET, and satellites like TROPOMI and TEMPO. This integration will support the validation of satellite‑based air quality observations. The position also includes responsibilities related to managing and enhancing a NASA‑backed sensor and remote sensing database, including work with ArcGIS, spatial interpolation techniques (e.g., kriging), and data visualization.

The Trace Gas Group values diverse backgrounds and perspectives, and encourages the development of side projects that promote collaboration both within NASA Ames and with external partners.

Required Qualifications
  • PhD in engineering, data/physical sciences (e.g., Chemistry, Physics, Atmospheric Sciences)
  • Laboratory or field experience with atmospheric measurements
  • Familiarity with analytical instruments for air quality monitoring
  • Ability to integrate multiple data streams for scientific analysis
  • Strong communication skills and ability to work in collaborative environments
  • Willingness to occasionally travel for field deployments
Preferred Qualifications
  • Proficiency in data analysis tools
  • Experience with collaborative scientific work
  • Knowledge of machine learning, data assimilation, ArcGIS, or NASA satellite data platforms
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