The ECosystem Analytics and Intelligence (ECAI) lab at the University of Wisconsin-Madison
(UW-Madison) is seeking one Ph.D. research assistant and two postdoctoral associates to join our
team in advancing hybrid AI modeling for agriculture and ecosystem sciences! Funded by NSF,
NASA, DOE, USDA, and industry partners, our lab spans the spectrum of ecosystem AI and
process-based modeling, data–model fusion, and cross-scale sensing. We are dedicated to advancing
science and technology to support global food security and environmental sustainability.
Candidates will apply knowledge-guided machine learning (KGML) techniques to enhance the
monitoring of carbon–water–nutrient cycles in agricultural and natural ecosystems. This work involves
integrating multi-modal data (remote sensing, EC flux towers, chamber measurements, soil sampling,
genomics, etc.), biogeochemical and physical process-based models, advanced AI algorithms, and
atmospheric inversions. Research topics include: Developing and implementing KGML frameworks to
refine U.S. cropland carbon budget estimates and improve process understanding to optimize
management strategies; Reducing uncertainties in estimating global GHG (CO₂, CH₄, N₂O) through
KGML and harmonized cross-scale observations; Developing AI-ready benchmark datasets and
open-source software to accelerate AI algorithm development and application in Earth system modeling;
AND pursuing additional research topics of mutual interest aligned with the lab’s overarching goals.
The position will be primarily supervised by the Assistant Professor Dr. Licheng Liu (Google Scholar,
Linkedin, Digital Agriculture Group), through the Department of Biological Systems Engineering (BSE),
and will work closely with diverse collaborators, including the University of Illinois Urbana-Champaign
(UIUC), National Oceanic and Atmospheric Administration (NOAA), Lawrence Berkeley National
Laboratory (LBNL), AI-LEAF institute, AI4NM working group, and beyond.
Essential Qualifications:
All applicants are expected to have a strong quantitative background (Bachelor’s or Master’s degree for
Ph.D. applicants, and Ph.D. degree for postdoc applicants), such as earth and atmospheric science,
computer science, hydrology, ecology, environmental science, physics, math, statistics, or other closely
related fields. A Ph.D. applicant should also meet the UW-Madison BSE admission requirements.
Successful candidates should demonstrate one or more of the following:
● Strong programming experience (e.g., Python, Fortran, C++) and familiarity with supercomputing
or cloud platforms.
● Experience with advanced AI/deep learning, particularly in scientific AI development/application.
● Knowledge of process-based models and data assimilation techniques.
● Excellent data visualization and communication skills.
● Experience in large-scale ecosystem modeling or GHG analysis.
Logistics:
● Ph.D. position: expected start Fall 2026; funding commitment for 4 years.
● Postdoctoral positions: expected start Spring 2026 (or earlier); funding commitment for 2 years,
renewable or promotable upon annual performance.
● Positions remain open until filled.
Application Process:
Qualified candidates should send (1) CV, (2) cover letter (1~2 pages), (3) latest transcripts, and (4) contact
information of three references to Dr. Licheng Liu (licheng.liu@wisc.edu) by December 31, 2025 for full
consideration.
● Email subject line: [Name] + [Ph.D./Postdoc Application] (e.g., Jane Doe – Ph.D. Application).
● Selection process: Shortlisted candidates will be invited for an interview; successful candidates
will then be guided to complete the formal application through the UW-Madison system.
About the Author
