
Michigan State actively promotes a dynamic research and learning environment in which qualified individuals of differing perspectives and cultural backgrounds pursue academic goals with mutual respect and shared inquiry.
The position supports research on forecasting agricultural production and yields using geospatial data, machine learning, and ground-based measurements to understand the underlying mechanisms and develop predictive capabilities. The project aims to apply deep learning and artificial intelligence to make predictions using imperfect data and partial knowledge, leveraging their ability to continuously learn and adapt for improved forecasting.
Required skills and experience include:
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, citizenship, age, disability or protected veteran status.
Doctorate
The successful candidate is required to have a PhD with a quantitative background by the effective date of hire.
The required degree must be in the fields of agricultural science, machine learning, remote sensing of environment, ecosystem analysis, micrometeorology, quantitative modeling, or relevant fields (agriculture, ecology, natural science, etc.).
Must have at least one first authored publication in the peer reviewed literature.
Experience with interests and experience in quantitative analysis and field research.
The application should include:
12/22/2025
MSU strives to provide a flexible work environment and this position has been designated as remote-friendly. Remote-friendly means some or all of the duties can be performed remotely as mutually agreed upon.
Michigan State University has been advancing the common good with uncommon will for more than 160 years. One of the top research universities in the world, MSU pushes the boundaries of discovery and forges enduring partnerships to solve the most pressing global challenges while providing life-changing opportunities to a diverse and inclusive academic community through more than 200 programs of study in 17 degree-granting colleges.
