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University of Missouri-Saint Louis · 1 week ago

Post-Doctoral Associate in Geospatial Artificial Intellegence (GEOAI) (One-Year Appointment, Renewable Based on Funding Availability)

St Louis, MO

Full-time

Onsite

Senior Level

The University of Missouri–St. Louis (UMSL) is inviting applications for a Post-Doctoral Associate in GeoAI. This research-focused position offers an opportunity to advance innovative research in Geospatial Artificial Intelligence, collaborating with experts from UMSL and the National Geospatial-Intelligence Agency (NGA).

EducationHigher EducationUniversities

No H1B

U.S. Citizen Only

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

Qualification

AI/ML/DL model developmentGeospatial data analysisPython programmingTensorFlowPyTorchRemote sensing expertiseCloud computingResearch experienceCollaboration skillsCommunication skills

Required

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