Job Title: Postdoctoral Research Fellow in Geomatics (1)
Location: Saskatoon
Company: Super GeoAI Technology Inc.
Role
We are seeking a Postdoctoral Research Fellow in Geomatics to lead AI-driven geospatial research and development in collaboration with university partners and Mitacs. The fellow will focus on advancing methods for field boundary detection, land-use classification, and change detection to enable more accurate crop monitoring, yield prediction, and risk assessment. A key responsibility of this role will be to lead the collection, curation, and development of AI training datasets to support SGA’s AI algorithm team. This position combines applied geomatics research with cutting-edge AI/ML, bridging academic innovation with real-world applications in agriculture and crop insurance.
Key Responsibilities:
- Lead applied research projects in geomatics, remote sensing, and geospatial AI for agricultural applications.
- Design and implement methods for field boundary detection, land cover classification, and temporal change analysis.
- Collect, curate, and develop AI training datasets to support model training and validation.
- Analyze and integrate multi-source geospatial data, including satellite imagery, drone data, LiDAR, climate, and agricultural datasets.
- Develop and validate AI/ML models to process and interpret large-scale geospatial data.
- Collaborate with AI engineers, GIS developers, and data scientists to integrate research outputs into SGA’s commercial platforms.
- Publish research findings in peer-reviewed journals and present at academic and industry conferences.
- Mentor graduate students and research assistants engaged in Mitacs-supported projects.
- Engage with industry stakeholders (farmers, insurers, agri-tech partners) to validate solutions and ensure adoption.
Qualifications:
- Ph.D. in Geomatics, Remote Sensing, Geography, Geospatial Science, or a related field.
- Must have received (or expect to receive) a Ph.D. between October 2020 and December 2025.
- Strong background in remote sensing, photogrammetry, or geospatial data analysis.
- Experience working with satellite imagery, drone data, or LiDAR for large-scale applications.
- Proficiency with geospatial software and tools (e.g., ArcGIS, QGIS, GDAL, ENVI).
- Demonstrated ability to design experiments, analyze datasets, and validate AI/ML models.
- Strong publication record in peer-reviewed journals.
- Excellent communication and collaboration skills, with experience working across academic, research, and industry teams.
- Ability to work independently while advancing both research innovation and practical applications.
This isn’t just academic research—you’ll be pioneering geospatial AI that powers the next generation of crop monitoring, yield prediction, and agricultural risk management.