Graduate Research Assistant position in ecological modeling

Graduate Research Assistantship (MS or PhD)


 Ecological Modeling – Sim4est


The Forest Advanced Computing & Artificial Intelligence Lab (FACAI) at Purdue University is seeking applicants for a Graduate Research Assistant position in ecological modeling. The successful candidate will work with the global forest expert team in Science-i to participate in a research project on modeling global forest dynamics (Sim4est), sponsored by the World Resources Institute.   

The desirable starting time is early 2023, but can be flexible.


Graduate Research Assistant will receive full salary and benefits (medical insurance etc.), plus tuition remissions. The total award package is worth $61,464 – $70,000 per year.

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 B.S. in forestry, ecology, modeling, computer science, statistics, 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 resume, b) a Research Statement outlining the candidate’s research interests and qualifications, c) unofficial transcripts, and d) contact information of three references, should be sent to the email address listed below. Successful candidates who have passed the initial screen will be invited to submit a formal application to Purdue University Graduate School.

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


Dr. Jingjing Liang

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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