Postdoctoral Research Fellow, Environment and Sustainability Studies

Wake Forest University; Winston-Salem (NC); On-site; USD 50,000 - 70,000; Full time

Job summary

Wake Forest University in Winston-Salem, NC, is seeking a postdoctoral research fellow to conduct cutting-edge research on remote sensing and tropical forest carbon. The role involves developing advanced algorithms, conducting field campaigns, and preparing scholarly articles.

Applicants should hold a PhD or ABD in related fields and have strong skills in geospatial analysis and machine learning. This position is full time and allows for collaboration with a leading research team.

Qualifications

• Strong publication record in remote sensing, forest ecology, and applied machine learning.
• Demonstrated experience in planning and executing field data collection using drones or terrestrial lidar.
• Outstanding skills in interpersonal communication and scientific writing.

Responsibilities

• Develop and implement advanced AI and machine learning algorithms for analyzing remote sensing data.
• Plan and conduct field campaigns to collect high-resolution ecological data.
• Support technical proposal preparation for grant funding.

Skills

Geospatial analysis

Applied machine learning

Deep learning

Forest ecology

Remote sensing data processing

Education

PhD or ABD in Environmental Science, Forestry, Geography, Earth System Science, Computer Science

Tools

Python

R

Google Earth Engine

Job description

Job Description Summary

Wake Forest University invites applications for a postdoctoral research fellowship. The appointed candidate will collaborate closely with Dr. Ovidiu Csillik and collaborators to conduct cutting‑edge research at the intersection of remote sensing, tropical forest carbon, and artificial intelligence (AI). The lab focuses on leveraging airborne and spaceborne lidar (such as GEDI), alongside field inventory measurements, to map and monitor forest degradation and carbon dynamics in tropical ecosystems. We particularly welcome applicants possessing a strong foundation in geospatial analysis, applied machine learning/deep learning, forest ecology, and large‑scale remote sensing data processing.

The successful candidates will participate in preparing presentations and scholarly articles for publication in high‑tier journals. Additionally, the candidates will assist in mentoring research assistants and supporting the preparation of technical proposals.

This position is available on a one‑year contractual basis, with the possibility of extension based on performance and funding availability. The position is for 1 year.

Employment Terms

Applications will be accepted through June 30, 2026, 11:59 PM EST.

Job Description

This position is not eligible for sponsorship of non‑immigrant or immigrant visa status through Wake Forest University. All eligible applicants are encouraged to apply.

Essential Functions

• Develops and implements advanced statistics, AI, and machine learning algorithms to process and analyze large‑scale remote sensing datasets, specifically airborne lidar and spaceborne lidar (GEDI).
• Integrates field inventory measurements with remote sensing data to model tropical forest carbon stocks and monitor forest degradation.
• Plans and conducts field campaigns to collect high‑resolution structural and ecological data using drones (UAVs) and terrestrial lidar systems.
• Writes project reports, journal articles, conference papers, and presentations to disseminate research findings.
• Supports technical proposal preparation for developing new projects and securing grant funding.
• Contributes to the training and mentoring of undergraduate research students in the lab.

Required Education, Knowledge, Skills, Abilities

• PhD or All but Dissertation (ABD) in Environmental Science, Forestry, Geography, Earth System Science, Computer Science, or other closely related disciplines.
• Strong publication record in the areas of remote sensing, forest ecology, carbon modeling, or applied machine learning.
• Demonstrated experience in planning and executing field data collection using drones and/or terrestrial lidar.
• Demonstrated skill in developing code for geospatial data analysis and machine learning using Python, R, and Google Earth Engine.
• Profound knowledge and hands‑on experience in processing airborne lidar and spaceborne lidar (GEDI) datasets.
• Experience with field inventory data and statistical approaches for scaling plot‑level measurements to regional or global scales.
• Outstanding skills in interpersonal communication, scientific writing, and effective time management.
• Capability to work independently and collaboratively in a cooperative team setting.

Preferred Education, Knowledge, Skills, Abilities

• Specific research experience working with tropical forest ecosystems and mapping forest degradation.
• Proficiency with advanced computer vision and deep learning techniques applied to satellite imagery and 3‑D point cloud data.
• Experience with high‑performance computing (HPC) or cloud computing environments for handling massive geospatial datasets.
• FAA Part 107 Remote Pilot Certificate for commercial drone operations.

Accountabilities

• Responsible for own work.

Physical Requirements

• Moderate physical activity: Mainly working on computer algorithms and large‑scale data analysis. Conducting fieldwork may require hiking, carrying equipment (such as drones), and navigating forested environments.

Environmental Conditions

• No environmental conditions.

Additional Job Description

Full time.

This position profile identifies the key responsibilities and expectations for performance. It cannot encompass all specific job tasks that an employee may be required to perform. Employees are required to follow any other job‑related instructions and perform job‑related duties as may be reasonably assigned by his or her supervisor.

In order to provide a safe and productive learning and living community, Wake Forest University conducts background investigations and drug screens for all final staff candidates being considered for employment.

Equal Opportunity Statement

The University is an equal opportunity employer and welcomes all qualified candidates to apply without regard to race, color, religion, national origin, sex, age, sexual orientation, gender identity and expression, genetic information, disability and military or veteran status.

Accommodations for Applicants

If you are an individual with a disability and need an accommodation to participate in the application or interview process, please contact [e-mail] or (336) 758‑4700.