Research Scientist in Ecosystem Modeling - Institute Sustainability, Energy Environment

Agroecosystem Sustainability Center (ASC)

This position may be eligible for a hybrid or remote work arrangement dependent with unit operational needs.

Lead research projects on sustainable agriculture and global environmental change regarding productivity and environmental sustainability in agroecosystems across a variety of scales from the field, regional to the globe using the tools of advanced ecosystem models, machine learning, data assimilation, and high‑performance computation, with constraints from satellite observations and in‑situ measurements. Publish research output in academic journals and conferences, lead on project management and student/postdoc mentoring, and prepare and complete proposal writing.

• Research:
  • Conduct field‑to‑regional‑scale modeling of productivity and environmental sustainability of agroecosystems using advanced ecosystem models constrained by in‑situ observations and satellite products.
  • Publish and disseminate research outputs in journals and at conferences.
  • Write proposals to secure continuous research funds.
• Project Management:
  • Lead and manage research projects.
  • Support research team management and student/postdoc mentoring.
  • Manage computing resources and onboard new team members in computing.

• Ph.D. degree and at least one year of postdoctoral experience in ecosystem modeling, environmental science, earth system sciences, or a related field.
• Experience using advanced agroecosystem models, ideally the ecosystem model, to simulate productivity and ecosystem services that guide improved management practices at large scales.
• Experience applying data assimilation and using observations from in‑situ sensors or satellite products (e.g., gross primary productivity, leaf area index, yield, GHGs) to quantify productivity and ecosystem services through process‑based modeling, such as hydrological or agroecosystem modeling.
• Experience using surrogate models to improve the efficiency of process‑based models.
• Experience with data assimilation, machine learning, and optimization techniques.
• Experience in student mentoring.
• Publications in leading journals within the field.

• Ph.D. in Environmental Modeling.
• More than 5 years research experience in hydrological/agroecosystem modeling.

• Required:
  • Knowledge of agroecosystem modeling, optimization algorithms, and high‑performance computing.
  • Excellent written communication skills, with a record of publications in peer‑reviewed journals.
  • Knowledge and experience with office software and the ability to learn custom systems.
  • Ability to manage multiple priorities independently and meet deadlines.
  • Demonstrated ability to exercise sound judgment, discretion, and tactful communication.
  • Strong organizational skills, with attention to detail and accuracy.
  • Proven ability to adapt to new challenges and responsibilities.
  • Commitment to collaborative work with faculty, staff, and research partners to advance shared goals.
  • Evidence of accountability, professionalism, and ownership in all work.
  • Demonstrated ability to foster a respectful and inclusive work environment through effective interpersonal skills, collaboration, and professional engagement with colleagues and stakeholders.
• Preferred:
  • In-depth knowledge of agroecosystem modeling, crop physiology, and biogeochemistry.

100% full‑time Academic Professional position, appointed on a 12‑month basis. The expected start date is as soon as possible after the close date. The budgeted salary range is $65,000 to $95,000. Salary is competitive and commensurate with qualifications and experience, while also considering internal equity. This position is eligible for benefits, including Health, Dental, Vision, Life Insurance, a Retirement Plan, Paid time Off, and Tuition waivers for employees and dependents.

Applications must be received by 6:00 pm (Central Time) on Monday, March 9, 2026. Apply for this position using the Apply Now button at the top or bottom of this posting. Applications not submitted through (Use the "Apply for this Job" box below). will not be…