Post-Doctoral Associate

The research will focus on hybrid AI modeling and agroecosystem sustainability, in collaboration with the AI-CLIMATE Institute (https://cse.umn.edu/aiclimate). The role involves building knowledge-guided machine learning (KGML) models for sustainable agricultural practices, developing AI-ready benchmark datasets, and reducing the uncertainty of national greenhouse gas (GHG) inventories.

Duties/Responsibilities

70% Primary Research Focus: This postdoctoral associate will apply advanced knowledge-guided AI-modeling techniques to expand and enhance the robust monitoring of cropland carbon budgets. This involves integrating multi-modal data (e.g. remote sensing, eddy-covariance flux tower/chamber measurements, soil sampling), biogeochemical/physical process-based model, advanced AI algorithms, and top-down atmospheric inversions. Tasks Include: Developing AI-ready benchmark datasets to aid in the AI algorithms development/application within earth ecosystem modeling; Developing/implementing KGML-engaged framework to refine crop land carbon budget estimates and improve management strategies across the U.S. Heartland; Conducting local, regional, and global simulations to validate models and methodologies; Collaborating with the AI-CLIMATE institute to reduce uncertainties in national GHG inventories and develop knowledge-guided foundation models.

20% The postdoc will be expected to lead efforts or collaborate on research reports, peer-reviewed manuscripts for publication and invention disclosures, and participate in seminars, national and international conferences when needed. The postdoc is also invited to participate in, or initiate, further grant proposals to further fund this research.

10% Participation as an active member of the full research team, supporting all tasks as needed to support the research team as a whole. This includes providing training and mentorship to graduate and undergraduate students in the lab and participation in all activities or meetings organized by the lab, or departmental activities where postdoc participation is required.

Required

• Ph.D. in a quantitative discipline such as Earth and atmospheric sciences, environmental science, hydrology, ecology, computer science, math, statistics, or related fields.
• Strong programming experience (e.g., Python, Fortran, or C++) and familiarity with supercomputing or cloud platforms.
• Experience with AI/deep learning beyond simple tools (e.g., Random Forest, ANN), particularly in integrating physical models and AI algorithms.
• Knowledge of process-based models and data assimilation techniques.
• Excellent skills in data visualization and communication.

Preferred

• Experience in large-scale ecosystem modeling or GHG inventory analysis.
• Experience working on projects with policy or industry applications, particularly in agriculture.
• Demonstrated ability to publish peer-reviewed scientific manuscripts and collaborate on interdisciplinary research teams.
• Familiarity with uncertainty quantification and parameter calibration methods.

The Department of Bioproducts and Biosystems Engineering (bbe.umn.edu) is an internationally renowned academic unit with the core mission of sustainable use of renewable resources and enhancement of the environment. BBE is affiliated with both the College of Food, Agricultural and Natural Resource Sciences (CFANS) and the College of Science and Engineering (CSE).

Pay Range: $58,000 - $61,008 annually; depending on education/qualifications/experience

Please visit the Benefits for Postdoctoral Candidates website for more information regarding benefit eligibility.

• Competitive wages, paid holidays, and generous time off
• Continuous learning opportunities through professional training
• Medical, dental, and pharmacy plans
• Healthcare and dependent care flexible spending accounts
• University HSA contributions
• Disability and life insurance
• Employee wellbeing program
• Financial counseling services
• Employee Assistance Program with eight sessions of counseling at no cost

Applications must be submitted online. To be considered for this position, please click the Apply button and follow the instructions. You will have the opportunity to complete an online application for the position and attach a cover letter and resume.

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This position will remain open until filled.

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