The University of Minnesota (UMN), in collaboration with USDA Forest Service (USFS), is inviting a postdoctoral scholar to work on a project that examines how a state forest property tax program enrollment contributes to long-term carbon sequestration and storage. In addition, the project will offer insight into how other types of landowner incentive programs are/can be developed, implemented, and marketed to entice landowner enrollment and the production of co-benefits, such as carbon storage, associated with forest land conservation.
The successful candidate will be instrumental in advancing scientific understanding of the link between land-use policy and management and the provision of forest carbon storage and sequestration. Leveraging an innovative forest conservation program, Minnesota’s Sustainable Forest Incentives Act (SFIA), the post-doc and project collaborators will develop empirical models that estimate the probability forest land conversion among lands enrolled in the SFIA program and the program’s contribution to long-term carbon sequestration and storage. A successful candidate will have the knowledge,
skills, and ability to construct and evaluate metrics to identify urban land development pressure on forest conservation, and work with the project team in developing and evaluating empirical models.
The individual will be mentored by scientists in the Department of Forest Resources at UMN, as well as the USFS Southern Research Station (SRS) and Northern Research Station (NRS). The location of this position will be either the University of Minnesota (St. Paul, Minnesota) or the USFS SRS Forestry Sciences Laboratory (Research Triangle Park, North Carolina). The decision on where the position will be located will be made at the time an employment offer is extended. The position has considerable flexibility in the extent of work that can be performed remotely.
Roles/Responsibilities
- Lead development of geospatial data using advanced analytical and statistical techniques with a focus on land-use policy. (30%).
- Generate spatially explicit variables as proxies for urban development pressure on forest land using advanced geospatial techniques. (20%).
- Collect, process, and analyze parcel level data from various sources including remote sensing, surveys, and public records. (20%).
- Work collaboratively with other researchers on the project team. (15%).
- Prepare reports, manuscripts, and presentations of research findings for publication and conference presentation. (10%).
- Professional and Career Development. (5%)
Eligibility
- A Ph.D. in forestry, environmental science, or natural resources with disciplinary expertise in geospatial sciences, applied economics, computer science, or advanced statistics, or a related discipline.
- Experience with remote sensing, GIS, and spatial statistics.
- Expertise in geospatial analysis and modeling.
- Proficiency in programming languages such as Python, R, and/or MATLAB.
Requirements
- Experience with geospatial software such as ArcGIS and/or QGIS.
- Experience with statistical software tools such as R, SAS, STATA.
- Excellent communication skills and ability to work collaboratively with others.
- Strong problem-solving skills and attention to detail.
Application Details
- Cover letter
- CV/resume
- Graduate transcripts
- List with the contact information for three references.
For further information about the application process, contact Dr. Michael Kilgore ( mk******@um*.edu ), Professor, Department of Forest Resources, University of Minnesota.
