College of Agriculture & Natural Resources Department of Forestry

Institute for Digital Forestry Postdoctoral Fellow

Hiring Organization: Purdue University
Employment type: Full-Time
Application Due Date: January 2, 2025

The Purdue University Institute for Digital Forestry invites applications for multiple postdoctoral positions. Successful applicants will become part of a multidisciplinary cohort, collectively addressing research areas of interest. Fellows will be co-mentored by faculty of different disciplines and include development of both technical and professional skills to ensure the most successful outcome for individual growth and career preparation. The Institute for Digital Forestry is a transdisciplinary collaboration of over 30 investigators from the colleges of Agriculture, Engineering, Liberal Arts, Libraries, Polytechnic and Science that integrates expertise in AI/ML, computer applications and modeling, geosciences, satellite and drone sensing platforms, social sciences, education, and forest biology, ecology, health, and management for sustainable and equitable rural and urban forest management.

Position Title: Institute for Digital Forestry Postdoctoral Fellow

Required Qualifications: We seek highly motivated, well-organized individuals with strong quantitative skills to work on funded disciplinary and interdisciplinary projects and assist development of additional funded programs. A PhD in a discipline appropriate to the specific research is necessary.

Biodiversity coupling: Investigate the coupling of below and above ground biodiversity in forest ecosystems across the continental U.S. This involves modeling of connections between above and below ground biodiversity in forest ecosystems and the patterns and drivers for this above-below-ground coupling. Above-ground data will be based primarily on USDA Forest Service tree inventory data and below ground data will be derived from soil DNA sequencing. The postdoc will be hosted in the Songlin Fei lab (Forestry & Natural Resources), with collaborations with University of Tennessee, Indiana University, the Smithsonian Institute, University of Texas, El Paso, and the USDA Forest Services. A PhD in ecology, forestry, or biology is required with expertise in mycorrhizal ecology, forest ecology, modeling, and/or spatial analysis. Experience with R programming, GIS, and other analytical tools and experience in handling large mycorrhizal data sets are highly desirable. Ability to work with researchers across a variety of disciplines is required.

Ecological and environmental parameterization: Utilize ecological and environmental data to parameterize and define “what if” scenarios and models that increase forest carbon stocks. The Fellow will be responsible for compiling existing datasets, and when applicable, generating new datasets that optimize Carbon Smart Commodity management practices under current and future conditions. The postdoc will be hosted by Brady Hardiman and Morgan Furze (Forestry & Natural Resources). Relevant PhD fields are forestry or ecology, with an emphasis on carbon ecology, silviculture, and/or forest modeling.

Forest management practices modeling: Examine scenarios applying management practices from individual stands to the regional landscape using FVS, LANDIS, or other models in order to balance among carbon sequestration and other ecological values and services (resilience, diversity, wildlife, etc.). Comparisons will be made relative to a no action reference alternative. The project will require some fieldwork on forested sites in southern Indiana. The postdoc will be hosted by Mike Saunders and Mike Jenkins (Forestry & Natural Resources). Relevant PhD fields are forestry or ecology, with an emphasis on carbon ecology, silviculture, and/or forest modeling. Experience with FVS, LANDIS, and other forest growth and yield programs is desirable. Ability to supervise field technicians and collect field data is required.

Optical remote sensing. Develop, implement, and test signal and data processing algorithms to exploit various earth observation data in support of carbon/biomass mapping in temporal and tropical forests. Apply advanced vision and language models to enhance remote sensing foundation models for cross-scale landscape ecology and land cover classification. This position is also responsible for project management, data governance, and opportunities to

mentor undergraduate and graduate students in Forestry & Natural Resources, Computer and Information Technologies, and Civil Engineering. The postdoc will be hosted by Gang Shao (School of Information Studies) and Songlin Fei (Forestry & Natural Resources), with collaborations with Purdue Digital Forestry research groups, University of Maine, University of Tennessee, and Michigan State University. A Ph.D. in remote sensing, forestry, engineering, or related field is required with expertise on optical remote sensing data processing and analysis. Experience on Landsat, Sentinal-2 and NAIP, remote sensing foundation models, and programming in Python is highly desirable. Knowledge on SAR and lidar is a plus.

Date of Appointment: Available immediately

Review Date: Review of applications will begin in January 2025 and continue until the positions are filled.

Duration of Appointment: Initial appointments are for 24 months subject to satisfactory performance review at 12 months. Some positions may be renewed beyond 24 months based on available funding.

Salary: Purdue University provides a competitive annual stipend plus health care benefits.

To apply, please send statement of interest, curriculum vitae, and the names and contact information of three references to:

Nancy Cramer
Senior Administrative Assistant
Agricultural Research & Graduate Education
(765) 496-5038 office | (765) 426-0330 cell | njcramer@purdue.edu

 

Purdue University is an equal opportunity/equal access/affirmative action employer fully committed to achieving a diverse workforce.