The University of Minnesota Department of Forest Resources and USDA Forest Service, Northern Research Station are seeking a Researcher 6 to support forest carbon estimation and research for the United States’ National Greenhouse Gas Inventory. The individual will assist a team of scientists and analysts from the University of Minnesota and USDA Forest Service to develop improved estimation and reporting frameworks for carbon stored in forests. The individual will develop scientific approaches for improving forest carbon estimation which can be used in multiple reporting instruments. Topics requiring investigation, which are flexible and dependent on the individual’s background and interests, include improved estimation of forest land area, impacts of land use and land use change on forest carbon stocks and fluxes, and application of remote sensing and/or spatial statistics to address inconsistencies in forest carbon estimation. The position consists of summarization and statistical analysis of forest inventory data (60%) and writing and serving as a lead author on several peer-reviewed research publications (40%). The individual will use statistical techniques (e.g., spatial regression and machine learning) to develop models of forest carbon stocks and fluxes across the United States.
The position is available immediately and includes 1.5 years of funding and health insurance. Future funding is contingent on satisfactory progress and success in securing additional funds. The individual will be located on the St. Paul Campus of the University of Minnesota. Required Qualifications: PhD in forestry, natural resources, geospatial sciences, statistics, or a closely related field. The ideal applicant will have experience with statistical techniques and employing large datasets such as Forest Inventory and Analysis information to address research questions. Applicants should also have a strong work ethic, be able to work independently and cooperatively with researchers and analysts, and have a demonstrated writing and quantitative capability. Preferred Qualifications: Proven experience with analyzing remote sensing (e.g., Landsat and lidar) and forest inventory datasets as documented through published journal articles. Past experience and training in spatial statistics is ideal. Application Instructions: Interested applicants should supply all application materials to the UMN Job Site. Review of applications will begin immediately. The position number is 324606. Please submit a CV and cover letter to the position announcement: https://www.myu.umn.edu/psp/psprd/EMPLOYEE/EMPL/c/HRS_HRAM.HRS_APP_SCHJO B.GBL? Page=HRS_APP_JBPST&Action=U&SiteId=1&FOCUS=Applicant&JobOpeningId=324606 &PostingSeq=1 Any offer of employment is contingent upon the successful completion of a background check. Our presumption is that prospective employees are eligible to work here. Criminal convictions do not automatically disqualify finalists from employment. The position will be open until filled. Formal applications must be completed through the University of Minnesota on-line employment site (http://www1.umn.edu/ohr/employment/index.html). A cover letter including interest in the position, resume/CV, and names and contact information for three references are required. If you have questions, please contact Matthew Russell, 612-626-4280, russe...@umn.edu and Grant Domke (gmdo...@fs.fed.us).
