Post-Doc position in ecological modeling

Postdoctoral Research Associate


Ecological Modeling – Sim4est

The Forest Advanced Computing & Artificial Intelligence Lab (FACAI) at Purdue University is seeking applicants for a Postdoctoral Research Associate in ecological modeling. The successful candidate will coordinate with the global forest expert team in Science-i (see the map below for the global distribution) to lead a research project on modeling global forest dynamics (Sim4est), sponsored by the World Resources Institute.   

Desirable starting time is early 2023, but can be flexible.


Postdoctoral Research Associate will receive annual compensation of ca. US $52,000-$55,000 with benefits (Insurance, Retirement, Leaves, Paid Parental Leave, Paid holidays, etc. as per Purdue University policy). The initial appointment is for 24 months. Additional support may be available pending funding availability and satisfactory performance.

Successful candidates will be equipped with cutting-edge data packages, data management tools, and high-performance computing facilities to conduct top-tier research, and publish in high-impact journals – a solid foundation for one’s future science career.

In addition, successful candidates will work with global forest science communities in a multi-language and multi-culture setting, with abundant chances to serve and support under-represented researchers around the world.   


The successful candidate is expected to coordinate with the FACAI team in developing a leading research program Sim4est that simulates and projects global forest carbon dynamics with improved accuracy. To achieve this. the successful candidate will integrate in situ forest inventory data and remote sensing data in an artificial intelligence-based framework designed by Dr. Jingjing Liang. Experience with data query and data analytics, together with good communication skills will be essential for success in this position.


A Ph.D. degree in remote sensing, forestry, ecology, data science, or related fields is required.

Candidates will be evaluated based on the following criteria:

  • Experience with data query and data analytics, especially with regard to forest inventory data
  • Ecological modeling background and other quantitative skills,
  • Passion for path-making research,
  • Passion to serve and support the global forest research community,
  • Oral and writing proficiency.


A single pdf file containing a) the applicant’s CV, b) a Vision Statement outlining the candidate’s research interests and qualifications, especially with regard to the foregoing criteria, and c) contact information of three references, should be sent to the email address listed below.

All individuals, including minorities, women, individuals with disabilities, and veterans are encouraged to apply. Purdue University is an EEO/AA employer.



Dr. Jingjing Liang  jjliang at

Associate Professor of Quantitative Forest Ecology,

Dept. of Forestry and Natural Resources, Purdue University

Background: Forest Advanced Computing & Artificial Intelligence Laboratory (FACAI) employs the paradigm of Artificial Intelligence (AI) encompassing different state-of-the-art machine learning and statistical methods to study global, regional, and local forest resource management and biodiversity conservation.

Science-i is an international research hub hyper-converged with earth-observation data, global expertise, and advanced cyberinfrastructure to accelerate science by empowering underrepresented communities in global research and knowledge co-production.

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