USGS Assessing Impacts of Microbial Manipulations Native Plant Restoration

How to Apply

To submit your application, scroll to the bottom of this opportunity and click APPLY.

• An application
• Unofficial transcript or a copy of the student academic records printed by the applicant or by academic advisors from internal institution systems. See the detailed information on acceptable transcripts.
• A current resume/CV, including academic history, employment history, relevant experiences, and publication list.
• Two educational or professional recommendations.

All documents must be in English or include an official English translation.

U.S. Department of the Interior (DOI)

DOI-USGS-2026-19

Applications will be reviewed on a rolling basis.

The opportunity is located at the U.S. Geological Survey (USGS) in Ann Arbor, Michigan.

The USGS mission is to monitor, analyze, and predict current and evolving dynamics of complex human and natural Earth-system interactions and to deliver actionable intelligence at scales and time frames relevant to decision makers. As the Nation's largest water, earth, and biological science and civilian mapping agency, USGS collects, monitors, analyzes, and provides science about natural resource conditions, issues, and problems.

Northern wild rice (Zizania palustris, manoomin) is a native plant of great cultural significance to indigenous communities in the Great Lakes region. Its restoration is a priority for tribes and state resource managers across the Great Lakes basin. The USGS GLSC has partnered with the Bay Mills Indian Community since 2023 to explore the role that microbial communities play in restoration success of manoomin.

Field surveys of soil, water, and plants were conducted over two seasons. Manipulative experiments were performed to understand the impact of microbes and site conditions on germination and growth.

You will gain experience using these existing datasets, possibly supplemented by new data, to explore patterns in microbial (bacterial and fungal) communities between differing site conditions, plant health, and experimental manipulations. These patterns will give valuable insights to tribal partners for the next stage of our research into the roles of microbes in affecting restoration outcomes.

• Analyze microbial community data from environmental samples collected around native populations of northern wild rice using R and related statistical tools.
• Plan and implement microbial data analysis workflows in collaboration with USGS scientists and research partners.
• Collect soil samples for microbial and molecular analyses and conduct field techniques.
• Monitor mesocosm experiments manipulating soil microbiomes to improve wild rice health.
• Operate greenhouse research, including specimen care, experimental maintenance, and data collection.
• Perform soil molecular laboratory techniques to prepare samples for DNA metabarcoding and downstream analyses.
• Synthesize and communicate research findings through poster presentations and internal briefings for GLSC and partners.
• Use wetland ecology research methods, including innovative management strategies for invasive species such as Phragmites (e.g., microbial symbiosis and genetic biocontrol approaches).
• Conduct field research skills including plot setup, treatment application, and systematic ecological data collection throughout the field season.

The Great Lakes Science Center engages in partner-focused science, providing a unique opportunity to craft a research project and gain valuable experience in laboratory and field settings. You will collaborate closely with mentors to craft an experimental design and research plan that aligns with partner needs and is feasible in a single field season. You will gain experience with data collection, data management, and analysis.

Additionally, you will be able to present findings to relevant groups such as Michigan Wild Rice Initiative, U.S. Fish and Wildlife Service, and university partners.

DeWesley Bickford (wbickford)

June 15, 2026 (Start date is flexible and will depend on a…