Post-Doc Research Associate

The Department of Geography and Environment is calling for application for two post-doctoral fellows to work on a project funded by the US Department of Agriculture under the supervision of Prof. Conghe Song. One post-doc will focuse on remote sensing of vegetation, and the other will focus on ecosystem modeling. The remote sensing post-doc will be working on characterize forest canopy structure, including canopy height, tree crown size, leaf area index and aboveground biomass, using multiple sources of remotely sensed data, including very high-resolution imagery, lidar, radar and medium resolution optical data along with ancillary data. This post-doc will work closely with the other post-doc to be hired for the project, whose specialization will be remote sensing.. Both the remotely sensing and the ecosystem modeling products will be rigorously validated with ground observed data. The two post-docs will collaborate closely as they eventually will reconcile the remotely sensed data carbon storage with the ecosystem model estimated carbon storage for the same locations.

Required Qualifications for Remote Sensing Post-doc: 1. A PhD degree with an emphasis on remote sensing. 2. Experience of using multiple sources of remotely sensed data, particularly optical, Lidar, and Radar data. 3. Sound statistical skills and use of Machine Learning/Geospatial AI tools for data analysis. 4. Computer programing skills for remotely sensed data analysis. 5. Sound knowledge of remote sensing physics. 6. Experience working with ArcGIS Pro and Google Earth Engine are welcome.

Preference with be given to application who have relevant publications in the respective fields.

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