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Research Associate in Computational Spatial Science and Agricultural Insurance


The Department of Agricultural & Applied Economics along with an interdisciplinary team of researchers with expertise in applied economics and remote sensing led by Dr. Elinor Benami, based in Blacksburg, Virginia, is seeking a highly motivated individual to join our team as a Research Associate. The position is renewable up to three years, or potentially longer pending availability of continued funding.


As part of our NASA Harvest activities, our team is investigating the correspondence of remotely sensed indicators to realized losses of policyholders in a variety of agricultural insurance programs across the globe. The position requires evaluating variation in observable agro-environmental conditions as well as on-the-ground data related to yields and livelihoods.  The candidate will be responsible for supporting the research efforts of our team using a variety of tools and methods. These will include preparing geospatial and administrative data for analysis, applying theory-guided statistical approaches to uncover relationships in the data, generating visualizations and maps, preparing manuscripts for submission to peer-reviewed journals, and presenting findings to academic as well as practitioner audiences.

The successful candidate will have the opportunity to use their expertise in geospatial and economic analysis to assess the potential and limits of remotely sensed technologies to enhance the value of agricultural insurance to the public as well as policyholders. We anticipate occasional travel to visit relevant local partners as well as domestic and international collaborators for training and advancing the research program.

The ideal candidate will have an MS or PhD with relevant work experience in a relevant quantitative field, such as remote sensing, earth system sciences, computational social sciences, or agricultural economics/risk management, and a strong background in geospatial analysis & economic modeling. 

Location: Blacksburg, Virginia, with travel to collaborate with consortium partners expected.

Duration: Renewable up to three years.


  • Masters degree in a related field
  • Excellent written and oral communication skills
  • Demonstrated experience with data analysis software, such as R or Python
  • Facility with version control systems, e.g., Git
  • Interest in the scholarly as well as public policy applications and implications of computational spatial science


Preferred Qualifications

  • PhD in relevant field, including experience submitting academic papers for peer-reviewed publication
  • Experience with geospatial cloud computing platforms such as Google Earth Engine
  • Prior work in insurance/risk transfer 
  • Prior experience with techniques to measure agronomic losses

To apply: Please submit (1) a cover letter indicating your interests, relevant background, and contact information for 3 references (2) your CV (3) a link to your GitHub profile or similar coding portfolio that demonstrates relevant skills here: Applications will be reviewed on a rolling basis until filled, with a priority deadline of  Wednesday, January 31, 2024.

Contact Elinor Benami ( with further questions.

About NASA Harvest

NASA Harvest is NASA’s Global Food Security and Agriculture Program.

Our mission is to enable and advance adoption of satellite Earth observations by public and private organizations to benefit food security, sustainability, agriculture, and human and environmental resiliency worldwide. We accomplish this through a multidisciplinary and multisectoral Consortium of leading scientists and agricultural stakeholders, led by researchers at the University of Maryland and implemented through co-development with our partners across the globe.

About Virginia Tech

Virginia Tech is and has been pursuing a series of cluster hires to complement the strengths of existing faculty in pursuing interdisciplinary research the nexus of digital, biological, social, and physical sciences and engineering with application to agriculture, food, and natural resources. This vision aims to create a state and nation-wide network of interconnected faculty, partners, and resources for scientific discovery and developing and deploying new technologies. The goal is to increase overall efficiency, resiliency, sustainability, and economic value of food, agriculture production systems, and natural resources while expanding Virginia Tech’s global influence in this rapidly evolving domain. 

The successful candidate will have opportunities to contribute to the new Center for Advanced Innovation in Agriculture (CAIA), the Fralin Life Sciences Institute, and the CALS Center for Agricultural Trade to address emerging policy issues. The successful candidate may also forge research ties with other units on campus, such as the College of Engineering, College of Natural Resources and the Environment, the Global Change Center, the interdisciplinary graduate education program (IGEP) in remote sensing, the Institute for Society, Culture, and Environment (ISCE), and VT's Advanced Research Computing (ARC) center. 

Virginia Tech is located in Blacksburg, VA with a full-time student population of 33,000+ students. The Blacksburg campus is in a growth phase associated with significant public and private investments in computer and data science research and education. These investments include the construction of a Data & Decision Science Building that is part of a larger investment in developing a Global Business and Analytics Complex in Blacksburg.  Geographically, Blacksburg is nestled in the heart of the New River Valley, close to the Blue Ridge Mountains and the Appalachian Trail with ample outdoor recreation opportunities. 


In addition to the Blacksburg campus, VT operates a rapidly growing campus in the National Capital Region (Washington, D.C.) located in close proximity to multiple public agencies, research institutes, and private sector companies with an interest in geospatial data science.