"Post-Doctoral Associate in Geospatial Artificial Intelligence (GEOAI) (One-Year Appointment)"

Hiring Department

The UMSL Geospatial Collaborative at the University of Missouri–St. Louis (UMSL)

Job Description

The UMSL Geospatial Collaborative at the University of Missouri–St. Louis (UMSL) invites applications for a Post-Doctoral Associate in GeoAI. This is a full-time, 12-month research appointment beginning January 1, 2026 (or earlier by mutual agreement). The position is entirely research-focused, providing an exceptional opportunity to advance cutting-edge research at the intersection of Geospatial Artificial Intelligence (GeoAI).

The selected candidate will be based on-site in St. Louis, Missouri, under the supervision of Dr. Reda Amer, Director of the UMSL Geospatial Collaborative, and will collaborate closely with researchers and scientists from the National Geospatial-Intelligence Agency (NGA). This position is part of UMSL’s broader effort to strengthen partnerships with NGA and to support research in advanced remote sensing, geomatics, and geospatial intelligence within the rapidly expanding St. Louis Geospatial Ecosystem.

Key Responsibilities

• Conduct Advanced GeoAI Research: Lead and support original research projects applying machine learning (ML), deep learning (DL), and computer vision to geospatial and remote sensing datasets, including optical, SAR, and LiDAR imagery.
• Develop AI Models for Geospatial Applications: Design and implement AI-based algorithms for land cover classification, object detection, change detection, environmental monitoring, and geospatial data fusion.
• Collaborate with UMSL & NGA Researchers: Work closely with UMSL faculty, the UMSL Geospatial Collaborative team, and NGA scientists to align research with institutional and national priorities. Participate in joint technical discussions, workshops, and innovation activities.
• Data Processing and Integration: Preprocess and analyze large-scale geospatial datasets using Python, TensorFlow, PyTorch, ArcGIS, or QGIS. Develop data pipelines that integrate AI, remote sensing, and GIS workflows for operational geospatial applications.
• Dissemination of Research: Publish research findings in peer-reviewed journals and contribute to NGA Tearline and other open-source intelligence platforms. Present results at leading conferences such as GEOINT, AGU, IEEE IGARSS, and Esri UC.
• Mentorship and Engagement: Participate in UMSL Geospatial Collaborative seminars, workshops, and outreach initiatives. Mentor graduate and undergraduate students involved in GeoAI and remote sensing projects.

This position supports a project funded by the National Geospatial-Intelligence Agency, which limits participation in the project to citizens of the United States. As a result, only U.S. citizens are eligible for this position.

Qualifications

Required Qualifications

• Education: Ph.D. in Geospatial Engineering, Computer Engineering, Computer Science, Remote Sensing, Artificial Intelligence, Data Science, or a closely related field (completed by start date); ABD candidates with a scheduled dissertation defense before the appointment start date are also eligible.
• Technical Expertise: Proven proficiency in AI/ML/DL model development (e.g., CNNs, Transformers, Random Forests) and application to geospatial or remote sensing data.
• Programming Skills: Strong background in Python, TensorFlow, PyTorch, or Keras; familiarity with geospatial libraries and APIs (e.g., GDAL, rasterio, scikit-learn, OpenCV).
• Research Experience: Demonstrated research productivity through peer-reviewed publications, conference presentations, or technical reports.
• Collaboration & Communication: Excellent written and verbal communication skills; ability to work both independently and collaboratively with UMSL and NGA research teams.

Preferred Qualifications

• Experience integrating AI with remote sensing, LiDAR, or SAR datasets for geospatial intelligence or earth observation.
• Familiarity with cloud computing environments (e.g., AWS, Google Earth Engine, Azure AI) for large-scale geospatial analytics.
• Experience in big data analytics, data fusion, and geospatial automation workflows.
• Proven experience in proposal development, grant writing, or contributing to collaborative research projects.
• Prior experience collaborating with federal agencies (e.g., NGA, NASA, USGS) or defense-related geospatial projects.

Anticipated Hiring Range

Salary is competitive and commensurate with qualifications and experience. The University of Missouri System offers a comprehensive faculty benefits package, including health, retirement, and tuition assistance. For more information, please consult UMSL Human Resources and review the UMSL Faculty Benefits Guide (PDF).

Application Materials

Applicants should submit the following materials as PDF files via the UMSL careers portal: 1) Cover Letter: outlining qualifications and interest in the position. 2) Curriculum Vitae (CV). 3) A brief research statement or summary of past research accomplishments and future research goals; 4) Contact information for three professional references including the applicant’s Ph.D. advisor. For questions regarding this position, please contact: Dr. Reda Amer – Director, UMSL Geospatial Collaborative (Chair of the Search Committee) – Email: reda.amer@umsl.edu

Application Deadline

Review of applications will begin immediately and continue until the position is filled.

Sponsorship Information

This position supports a project funded by the National Geospatial-Intelligence Agency, which limits participation in the project to citizens of the United States. As a result, only U.S. citizens are eligible for this position.