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"Hydrologic Data Specialist"

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Hydrologic Data Specialist

Hydrologic Data Specialist

We are seeking a Hydrologic Data Scientist to support efforts underway at the Cooperative Institute for Great Lakes Research (CIGLR) and the NOAA Great Lakes Environmental Research Laboratory (GLERL) to develop next generation hydrologic and water level forecasting of the Great Lakes and advance ice data analysis. In this position, you will:

  • Advance runoff prediction capabilities for the Great Lakes basin by improving and extending existing modeling frameworks such as the Large Basin Runoff Model (LBRM) and data-driven Artificial Intelligence (AI) approaches, including Long Short-Term Memory (LSTM) networks and other machine learning models.
  • Generate and evaluate hydrologic hindcasts and forecasts to assess model fidelity, forecast reliability, and predictive skill across subseasonal to annual time scales.
  • Support operational transition and application of modeling and forecasting tools to partner agencies (U.S. Army Corps of Engineers), including integration of lake-to-lake routing and development of probabilistic prediction capabilities.
  • Collaborate in the co-development of decision support tools that translate model outputs into actionable information for regional stakeholders, building on priorities identified in previous engagement activities.

This position offers an opportunity to contribute to cutting-edge hydrologic modeling, AI-driven prediction, and decision support efforts aimed at enhancing water resource management across the Great Lakes.

In addition to hydrologic modeling and data analysis work, you will also be expected to attend collaborative meetings and provide progress updates, present results at scientific conferences (e.g., the International Association for Great Lakes Research), and help prepare manuscripts for publication in high-impact journals. You will be expected to work as part of an interdisciplinary team, as well as independently on individual job responsibilities and goals. In this position you will report to SEAS-CIGLR Assistant Research Scientist, Yi Hong.

Term Limited Appointment: This is a one (1) year term limited appointment, with an opportunity for extension based on funding and performance.

This position is open only to US Citizens or permanent residents due to federal security clearance required for access to NOAA GLERL facilities and resources.

Responsibilities:

  • Improve hydrologic and runoff modeling for the Great Lakes using tools such as LBRM and AI/ML approaches (e.g., LSTM).
  • Generate and evaluate hydrologic hindcasts and forecasts to assess model accuracy and reliability.
  • Support development of probabilistic lake-to-lake routing and forecasting capabilities for operational partners (e.g., U.S. Army Corps of Engineers).
  • Manage and analyze large hydrometeorological datasets from models, observations, and remote sensing.
  • Prepare technical reports, manuscripts, and presentations summarizing research outcomes.

Required Qualifications:

  • Bachelor's degree in hydrology, civil/environmental engineering, atmospheric science, data science, or a related field.
  • At least 1 year of related professional or academic experience.
  • Experience with hydrologic modeling and data analysis in Python, MATLAB, or similar environments. Experience with AI/ML applications in hydrology and environmental modeling preferred.
  • Strong quantitative, programming, and data management skills.
  • Familiarity with Great Lakes hydrology, water balance, or large-scale watershed modeling is desired, but not required.

Salary: Salary will be determined based on experience.

How to Apply: Applications are welcomed and encouraged from all qualified individuals regardless of background and identity. To apply, please complete the application on the U-M Careers site. A one page cover letter is required for consideration for this position and should be attached as the first page of your resume. The cover letter should:

  • Address your specific interest in the position and outline your experience that is directly related to this position.
  • Describe in detail your experience that pertains to each of the required qualifications listed below.

At the University of Michigan School for Environment and Sustainability (SEAS), we are at the forefront of building a more sustainable and just world for all by transforming the impact of higher education and reimagining the future. To learn more about SEAS and our values, please visit our website at https://seas.umich.edu/about/seas-values.

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