| Purpose of the Position: |
The EarthRISE Project Office, within the Lab for Applied Science (LAS) under the Earth System Science Center (ESSC), is seeking a highly motivated Research Scientist with strong expertise in agricultural remote sensing, geospatial artificial intelligence, and applied decision-support tool development. A successful candidate will lead and execute applied research leveraging Earth observations to address complex, real-world challenges in agricultural monitoring, crop production systems, land management, conservation practices, drought-related agricultural risk, crop-water applications, and agricultural decision-making. This role requires strong domain expertise in agricultural applications, utilizing advanced remote sensing, modeling, and geospatial data science approaches to develop actionable information products for operational and stakeholder use. The ideal candidate will bring strong agricultural remote sensing foundations, creative problem-solving skills, and the ability to design scalable approaches for large-area agricultural monitoring. Additionally, the candidate may work with multi-source Earth observation datasets, including moderate-, high-, and very high-resolution public and commercial satellite data. A geospatial data expert who can apply sophisticated AI/ML techniques directly to Earth science and spatial datasets is sought rather than an AI/ML generalist.
Operating within Earth Action, the EarthRISE project office focuses on developing last-mile solutions, improving coordinated action across NASA Earth Science, and fostering workforce development. EarthRISE develops applied Earth observation solutions that support state, local, tribal, territorial, federal, and private-sector decision-makers across key Earth science application areas, including agriculture and food security.
The EarthRISE Project Office in Huntsville, AL, offers a flexible and dynamic work environment, with an in-house team of over 30 science professionals and numerous opportunities for growth and professional development. With a growing economy, diverse population, low cost of living, and vibrant city life, Huntsville is consistently ranked among the top places to live in the U.S.
Duties / Responsibilities:
• Execute applied research and co-develop Earth observation-driven solutions focused on agricultural applications for state, local, tribal, territorial, federal, and private-sector stakeholders.
• Develop, evaluate, and scale remote sensing, modeling, and geospatial analytics methods that support agricultural monitoring, assessment, and decision-making across diverse agricultural systems and geographies.
• Apply geospatial artificial intelligence and machine learning workflows to extract actionable insights from multi-source Earth observation datasets, including optical, thermal, radar, and high-resolution satellite imagery.
• Support applied research and application development related to agricultural conditions, production systems, land management, environmental risk, and agricultural resilience.
• Integrate Earth observation products with agricultural models, climate datasets, field observations, agricultural datasets, and stakeholder-provided information where appropriate.
• Translate complex Earth science data, geospatial products, and model results into actionable, last-mile intelligence and decision-support tools for end-users.
• Lead publications, data products, technical documentation, and presentations at scientific and stakeholder-focused conferences.
• Provide coordination support and capacity-building/knowledge-transfer activities with domestic partner organizations and end users.
• Contribute to cross-project collaboration, proposal development, and workforce development activities within EarthRISE and NASA Earth Action.
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| Minimum Requirements: |
• Master’s degree in Agricultural Engineering, Agronomy, Crop Science, Earth Science, Geospatial Science, Geography, Environmental Science, Remote Sensing, or a related discipline (Bachelor's degree and experience in a specialized area may be substituted for a degree).
• Minimum of 1 year of verifiable, full-time work experience in these disciplines.
• Strong understanding of agricultural systems and agricultural remote sensing principles, including large-scale geospatial analysis, crop-environment interactions, time-series interpretation, spatial and temporal scaling, uncertainty assessment, and decision-making applications.
• Demonstrated expertise in geospatial artificial intelligence, with a proven track record of applying machine learning and AI techniques specifically to spatial, temporal, and Earth observation data.
• Experience processing, analyzing, and deriving products from multi-source satellite imagery, including optical, thermal, radar, high-resolution, and/or very high-resolution datasets.
• Demonstrated proficiency with relevant agricultural remote sensing, geospatial modeling, time-series analysis, and applied decision-support workflows.
• Working knowledge of domestic agricultural decision-making contexts, including applied agriculture, food security, land management, environmental risk, and stakeholder-driven information needs.
• Demonstrated ability to think creatively and independently in developing applied Earth observation methods that can be adapted across regions, datasets, agricultural systems, and stakeholder needs.
• Skilled in the use of Python, R, cloud-based geospatial platforms, or other programming environments specialized for spatial data science, raster data processing automation, and machine learning pipelines.
• Excellent verbal and written communication skills to effectively collaborate with interdisciplinary science teams and translate technical concepts to non-technical domestic stakeholders.
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| Desired Qualifications: |
• A PhD in Agricultural Engineering, Agronomy, Crop Science, Earth Science, Geospatial Science, Geography, Environmental Science, Remote Sensing, or a related discipline is preferred.
• 2 or more years of experience working in these disciplines is desired.
• Experience working with NASA and/or other federal, state, local, tribal, or private sector organizations is desired.
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