Job Summary
The Purdue University Institute for Digital Forestry invites applications for a postdoctoral position. 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.
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.
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.
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.