Postdoctoral Researcher: Urban Stream Water Quality Investigation

University of Michigan-Ann Arbor

Ann Arbor, MI, USA 🇺🇸

How to Apply

Applications are welcome and encouraged from all qualified individuals regardless of background and identity. If interested, the following application materials should be emailed to Dr. Runzi Wang ([email protected]). Please include “Postdoc Position Application” in the subject line of your email.

  1. Cover letter describing general research interest
  2. CV
  3. One representative manuscript (preferably first authored and published)
  4. List of 3 references with contact information (email)

Job Summary

A postdoctoral position is available starting Fall 2021 in Runzi Wang’s lab at the School for Environment and Sustainability at the University of Michigan. I am looking for a highly motivated postdoc who will work on the topic of continental-scale urban stream water quality investigation, with urban form and climate variability as the main influencing factors of interest. The candidate will work together with Wang to investigate urban water quality management under a multidisciplinary sustainability framework using sophisticated analytical procedures. The position will require (1) excellent statistical knowledge and coding skills. (2) experience with manipulating a variety of environmental and socioeconomic datasets (e.g., land use and land cover, building footprint, climate and weather, etc.). Theoretical foundation of urban hydrology and urban sustainability is highly preferred. Potential tasks will include (1) Data curation of the continental-scale urban stream water quality dataset and the associated social and environmental drivers. (2) Algorithm development to investigate urban stream water quality with the high-dimensional drivers. (3) Scenario assessment and decision making under different climate change and urban development scenarios. In addition to research, the postdoc candidate will have the opportunity to mentor undergraduate and graduate students and work with the project team to develop future grants.

The position includes a salary of $51,800 per year and full benefits, including employee health insurance eligibility. Appointment is for one year with renewal for a second-year possible following performance evaluation and dependent on funding. This position can be performed remotely given a reliable internet connection and regular engagement with the project team.

Mission Statement

The School for Environment and Sustainability’s overarching mission is to contribute to the protection of the Earth’s resources and the achievement of a sustainable society.  Through research, education, and outreach, the faculty, staff, and students are devoted to generating knowledge and developing policies, techniques, and skills to help practitioners manage and conserve environmental resources to meet the full range of human needs on a sustainable basis.

Required Qualifications*

  • PhD in environmental science, geography, urban planning, landscape architecture, natural resources, computer science, data science, information science or related field is required
  • A strong interest in interdisciplinary research.  
  • Strong qualitative and quantitative analysis background
  • Familiarity with R or Python

Desired Qualifications*

Preference will be given to applicants with a strong theoretical foundation and research interest in either urban hydrology or environmental planning. Programming experience in Google Earth Engine, Python, and/or R is preferred.

Additional Information

About Dr. Runzi Wang

Dr. Runzi Wang ( is an Assistant Professor at SEAS. Wang is a transdisciplinary researcher who studies change in natural and urban environments across space and over time, with the objective to drive positive change with ecological planning and design strategies. Combining technologies such as big data, machine learning, remote sensing, and spatial statistics, her primary research explores how land cover change and urban development pattern influence stream water quality and stormwater quality at the watershed basis, together with a variety of environmental, climatic and sociocultural factors. By enhancing the interpretability of machine learning in its application to landscape architecture, the most innovative part of her research is to uncover the nonlinear relationships between environmental, technological and sociocultural dimensions of landscape systems.

Application Deadline

Application deadline is *July 15th* but applications will be reviewed as they are received. Please contact Dr. Runzi Wang ([email protected]) with questions regarding this position.

Job openings are posted for a minimum of seven calendar days. The review and selection process may begin as early as the eighth day after posting. This opening may be removed from posting boards and filled anytime after the minimum posting period has ended.

U-M EEO/AA Statement

The University of Michigan is an equal opportunity/affirmative action employer.