[ES_JOBS_NET] Two Postdoc Positions in AI for Agriculture and Earth System Modeling

[Zhenong Jin]

The Digital Agricultural Group at University of Minnesota-Twin Cities has *two
postdoc *positions open for candidates to work on hybrid AI modeling!
Leveraging
the recent AI boom to substantially improve Earth System Prediction is a
paradigm-shift topic in the coming decade. In particular, *Knowledge Guided
Machine Learning (KGML)* is a hybrid modeling approach that combines
physical/biogeochemical models with AI algorithms and has demonstrated
great potential in several geoscience disciplines. We would like to develop
and apply this approach to enhance the modeling of a range of processes
related to agroecosystem sustainability, with a focus on managing
greenhouse gases (GHGs) emissions and reactive nitrogen (N) and phosphorus
(P) losses, and their impact on the air and water quality of the earth
system. We would also like to develop methods to assimilate diverse data
(e.g. those from remote sensing, low-cost sensors) into hybrid models and
significantly improve the ability to predict complex interconnected
processes.

This post is looking for candidates to work on *AI for Agriculture and
Earth System Modeling*. Successful applicants will be supervised by Dr.
Zhenong Jin (http://jinlab.bbe.umn.edu/) through the College of Food,
Agricultural, and Natural Resource Sciences and work closely with diverse
academic and industrial collaborators.



*Essential Qualifications:*

All applicants are expected to have a strong quantitative background, and
graduate from quantitative majors such as earth and atmospheric science,
hydrology, ecology, environmental science, math, and statistics, or any
other closely related fields. Successful candidates will need to meet one
or more 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 deep understanding of process-based models;
applicants whose past research only involves running models at site-level
will not be considered;

●      Knowledge of machine learning *beyond* simple tools such as Random
Forest and ANN.

●      Strong skill in data visualization.



*Logistics: *The positions are expected to start in Spring 2022. The
positions are open till 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 annual performance.



*Application Process:* Qualified candidates must send a short introduction
email and CV to Dr. Zhenong Jin* (**jinzn at umn.edu <jinzn at umn.edu>**)*.
Qualified applicants will be immediately reviewed upon receiving the
application. For further questions related to the application, please feel
free to reach out to us.



*About the Lab: *We are a fast-growing group dedicated to advancing science
and technology for achieving food security and environmental sustainability.
We have rich resources from industry partners and sufficient funding
support from a list of federal agencies to explore interest-driven research
questions. Our group members spread across the spectrum of process-based
modeling, data-model fusion, and algorithm development for remote sensing. We
look forward to having you join us and tackle big challenges with
innovation!


-- 
Zhenong Jin
Assistant Professor
University of Minnesota - Twin Cities
Department of Bioproducts and Biosystems Engineering
Institute on the Environment Associates
http://jinlab.bbe.umn.edu/
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