Postdoctoral Research Associate in AI and Global Forest Ecology
Forest Advanced Computing and Artificial Intelligence (FACAI) Lab
Department of Forestry and Natural Resources, Purdue University
The Forest Advanced Computing & Artificial Intelligence (FACAI) Lab at Purdue University invites applications for a Postdoctoral Research Associate position in global forest ecology, with a focus on integrating advanced artificial intelligence (AI) techniques into ecological research. We are seeking highly motivated individuals passionate about leading transformative, global-scale forest science.
The successful candidate will coordinate and lead interdisciplinary teams across the Science-i global forest network, contributing to foundational research in forest ecology augmented by AI, remote sensing, and large-scale data analytics.
Research Focus
- Global patterns and processes in forest ecosystems
- Integration of AI and machine learning in forest ecological modeling
- Collaboration with international teams on large-scale data synthesis
- Leadership and capacity-building among underrepresented global scientists
Start Date & Duration
- Preferred start date: Fall 2025
- Applications reviewed on a rolling basis
- Initial appointment: 24 months, with possible extension contingent on performance and funding availability
Benefits & Support
- Competitive annual salary with full benefits (medical insurance, retirement plans, etc.)
- Access to cutting-edge datasets, data management platforms, and high-performance computing resources
- Professional development support: Publishing in high-impact journals, international collaboration, and global research leadership
- Work in a vibrant, multilingual and multicultural environment with strong global outreach
- Ph.D. in Computer Science, Artificial Intelligence, Data Science, Remote Sensing, Forestry, Ecology, or related disciplines
- Demonstrated research experience in quantitative modeling or AI applications
- Strong publication record and excellent communication skills
Preferred Qualifications
- Strong background in quantitative methods, machine learning, or ecological modeling
- Leadership experience in collaborative or international research projects
- Commitment to advancing equity and inclusion in global science communities
To apply, please submit a single PDF file containing:
- Curriculum Vitae (CV)
- Vision Statement outlining your research interests, relevant experiences, and how you meet the listed qualifications
- Contact information for three references
Send your application materials to:
Dr. Jingjing Liang
Associate Professor of Quantitative Forest Ecology
Department of Forestry and Natural Resources
Purdue University
Email: jjliang@purdue.edu
About FACAI
The FACAI Lab conducts globally consistent yet locally relevant forest research, combining AI with one of the world’s largest ecological datasets. Our achievements include:
- Estimating the total number of tree species on Earth
- Building the world’s most extensive forest inventory database
- Launching Science-i, a global platform empowering researchers worldwide