Dear All,

The Digital Agricultural Group at the University of Minnesota-Twin Cities 
is looking for two *postdoc *candidates to work on *AI for Agriculture and 
Earth System Prediction*. Research in our group spreads across the spectrum 
of process-based modeling, remote sensing, data-model fusion, and hybrid AI 
modeling. We are dedicated to advancing science and technology for 
achieving food security and agroecosystem sustainability.

*Leveraging the recent AI boom to substantially improve agroecosystem 
prediction is a paradigm-shift topic in the coming decade*. In particular, 
Knowledge Guided Machine Learning (KGML) as a hybrid modeling approach has 
demonstrated great potential in several geoscience disciplines. We would 
invite highly motivated applicants to further develop and apply KGML to 
investigate a range of critical questions concerning agroecosystem 
sustainability.

Successful candidates will be supported to work on one or more topics 
listed below:

● Develop AI-driven methods to assimilate remote sensing and low-cost 
sensor observations into KGML models to improve the prediction of GHG 
emissions, climate risks, and crop productions.
● The application of KGML for Climate-Smart Agriculture and optimizing 
management practices.
● Modeling the impacts of agricultural nitrogen (N) management on air and 
water quality.
● Modeling agricultural phosphorous (P) cycle, with a focus on P losses 
from cropland to water bodies and coupling with N cycle.
● GeoAI for commodity mapping and sustainable supply chain management

 The successful applicants will be supervised by Dr. Zhenong Jin (
https://bbe.umn.edu/people/zhenong-jin) and collaborate closely with 
leading experts from UIUC, Stanford, Lawrence Berkeley National Laboratory, 
and many more academia and industrial collaborators.



*Essential Qualifications:*All applicants are expected to have a strong 
quantitative background. The successful candidate will need to meet *at 
least two* of the following expectations:
● Strong programming experience (e.g., Python, Fortran, or C++) and be 
familiar with supercomputing and/or cloud platforms.
● Rich experience and code-level deep understanding of crop models or 
watershed models.
● Rich experience with remote sensing algorithm development.
● Familiar with deep learning algorithms and libraries such as PyTorch and 
TensorFlow, and have experience with GPU computing.

*About the Lab* (http://jinlab.bbe.umn.edu/): We are a fast-growing group 
who tackles big challenges with innovation! We have sufficient resources 
for supporting the exploration of high-risk high-reward ideas that can 
revolutionize digital agriculture. We collaborate closely with many leading 
groups in academia and the industry. What our work looks like? Please see 
our most recent publications in Nature Climate Change 
<https://www.nature.com/articles/s41558-022-01327-3>, Remote Sensing of 
Environment <https://doi.org/10.1016/j.rse.2022.112994>, and Geoscientific 
Model Development 
<https://gmd.copernicus.org/articles/15/2839/2022/gmd-15-2839-2022.html>.

*Applications*: Qualified candidates must send a short introduction email 
and CV to Dr. Zhenong Jin ([log in to unmask]). The interview will start 
immediately until all positions are filled. A competitive salary will be 
provided based on experience. The positions have a funding commitment for 
two years, with possibilities for renewal or promotion upon performance.

Best,
Jin