Dear Colleagues,
I’m writing to share a postdoc opening in my lab on a new NASA ecohydrology project. I would be grateful if you could circulate this announcement and encourage interested candidates to apply.
Review begins: June 1, 2026 (open until filled)
Thank you,
Kai
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Kai Zhu, PhD
Associate Professor
School for Environment and Sustainability
University of Michigan
The Zhu Lab at the University of Michigan School for Environment and Sustainability (SEAS) seeks a Postdoctoral Research Associate to work on causality detection in ecohydrological feedbacks relevant to rapid-onset (“flash”) droughts. The postdoc will be jointly
advised by Dr. Kai Zhu (University of Michigan) and Dr. Yanlan Liu (University of California, Los Angeles) and will be part of a broader NASA-funded project.
Research focus. The postdoc will develop and apply quantitative approaches to infer causal relationships among vegetation dynamics, hydroclimate conditions, and drought indicators across space and time. The project emphasizes integration of satellite remote
sensing, eddy-covariance/flux tower data, and reanalysis/land-surface products to understand land–atmosphere–vegetation interactions at subseasonal-to-seasonal timescales. Exact directions are flexible and will be shaped by the postdoc’s expertise and interests,
but will center on event-based ecohydrological dynamics (e.g., dry-downs following rainfall and/or heat pulses) and rigorous causal analysis beyond correlation.
Environment and collaboration. The position is based in-person in Ann Arbor, Michigan, at U‑M SEAS, with potential opportunities to visit UCLA for collaboration. The postdoc will also have opportunities to interact with NASA collaborators, including Dr. Alexey
Shiklomanov and Dr. Dhruva Kathuria (NASA Goddard Space Flight Center).
Qualifications. Applicants must have a Ph.D. (completed by the start date) in a relevant field such as ecohydrology, remote sensing, environmental science, ecology, atmospheric science, statistics, or a closely related discipline. We are especially interested
in candidates who demonstrate strengths in some combination of: (1) Quantitative/statistical modeling and/or machine learning (including time-series analysis); (2) Causal inference or related approaches for observational spatiotemporal data; (3) Working with
large environmental datasets (remote sensing, flux towers, reanalysis); (4) Land-atmosphere, hydrological, or plant physiological modeling; (5) Programming for scientific workflows (e.g., Python and/or R), reproducible research practices, and data processing.
Strong written and oral communication skills, as well as the ability to work effectively in a collaborative team, are essential.
Appointment. This is a 2-year postdoctoral position. The appointment will be made initially for one year, with the expectation of renewal for a second year contingent on performance and funding. Start date is flexible. Salary and benefits are competitive and
commensurate with experience, consistent with University of Michigan policies.
(1) Cover letter describing research experience, interests, and fit for the position; (2) Curriculum vitae; (3) Up to three representative publications (links are sufficient for published papers; for unpublished manuscripts, please include files); (4) Contact
information for three references.
Review of applications will begin on June 1, 2026, and will continue until the position is filled.