Postdoc: AI & Remote Sensing for Tropical Forest Carbon

Wake Forest University; United States; On-site; USD 54,000 - 70,000; Full time

Job summary

Wake Forest University invites applications for a postdoctoral research fellowship focused on remote sensing, tropical forest carbon, and AI. Collaborate with Dr. Ovidiu Csillik and team, leveraging GEDI and field data to map forest degradation and carbon dynamics in tropical ecosystems.

Candidates should excel in geospatial analysis, ML, and large-scale data processing, and contribute to publications. The position is a one-year contract with potential extension based on performance and funding.

Qualifications

• PhD or ABD in Environmental Science, Forestry, Geography, Earth System Science, Computer Science, or related field.
• Strong publication record in remote sensing, forest ecology, carbon modeling or ML.
• Experience with field data collection using drones and portable lidar systems.

Responsibilities

• Develops statistics, AI, and ML to process large remote sensing datasets (GEDI, airborne lidar).
• Integrates field inventory with remote sensing to model tropical forest carbon stocks.
• Plans field campaigns using UAVs and terrestrial lidar; writes reports and papers.
• Mentors undergraduate researchers and supports grant proposals.

Skills

Geospatial analysis

Python

R

Google Earth Engine

Education

PhD or ABD in Environmental Science/Forestry/Geography/CS

Tools

GEDI lidar

Drone data collection

Job description

Wake Forest University invites applications for a postdoctoral research fellowship focused on remote sensing, tropical forest carbon, and AI. Collaborate with Dr. Ovidiu Csillik and team, leveraging GEDI and field data to map forest degradation and carbon dynamics in tropical ecosystems.

Candidates should excel in geospatial analysis, ML, and large-scale data processing, and contribute to publications. The position is a one-year contract with potential extension based on performance and funding.