Postdoc Research Assoc in Geospatial AI (GeoAI) Forest Health

Job Summary

The Postdoctoral Research Associate will engage in research and development of a GeoAI-powered early warning system for forest health by integrating multi-source geospatial data, including satellite imagery, UAV-based LiDAR and multispectral data, and environmental datasets.

This position supports a USDA-NIFA funded project focused on detecting early indicators of forest stress, pest infestation, and environmental disturbances using advanced artificial intelligence and geospatial analytics. The role contributes to research, education, and extension activities in Missouri and supports the broader mission of advancing innovation in geospatial science and environmental monitoring.

ESSENTIAL JOB FUNCTIONS

• Plan and implement research activities focused on early detection of forest stress, disturbance, and ecological change using geospatial analytics and artificial intelligence.
• Compile, collect, clean, and process geospatial and ancillary datasets from multiple sources, including satellite imagery, UAV-based LiDAR, multispectral imagery, and environmental data.
• Develop, train, and optimize GeoAI models using machine learning and deep learning techniques for spatial analysis and predictive modeling.
• Validate GeoAI models through field verification and collaboration with the Missouri Ozark Forest Ecosystem Project (MOFEP).
• Develop decision-support tools and interfaces that translate complex geospatial outputs into usable information for stakeholders.
• Contribute to peer-reviewed publications, conference presentations, and technical documentation required for project deliverables.
• Mentor graduate and undergraduate students involved in research activities.
• Collaborate with interdisciplinary teams across research, extension, and education initiatives.
• Maintain accurate records of research activities, methodologies, and results.
• Perform other duties as assigned by the supervisor in support of project goals.

**KNOWLE