The Cooperative Institute of Great Lakes Research (CIGLR) is seeking candidates to join a team of hydrological modelers working on a series of projects related to the development, testing, and deployment hydrological models across the Great Lakes basin. Objectives of individual projects include calibration and verification of Weather Research and Forecasting (WRF)-Hydro and its meteorological forcings to support development of NOAA’s National Water Model, evaluation of potential empirical relationships between the risk of nutrient loading and land surface model parameters, and customization of WRF-Hydro to improve local flood forecasting capabilities.
The projects are expected to include partnerships with hydrological modelers at the University of Michigan and at the National Center for Atmospheric Research (NCAR) in Boulder, Colorado. The ideal candidates will have strong technical skills related to hydrological model development and high performance computing.
The successful applicants’ appointments will be with CIGLR, which is part of the University of Michigan’s School for Environment and Sustainability located in Ann Arbor, Michigan. CIGLR is a collaboration between the University of Michigan and NOAA that brings together experts from academia and government research labs to work on pressing problems facing the Great Lakes region. The candidate will spend the majority of their time at NOAA’s Great Lakes Environmental Research Lab (GLERL) in Ann Arbor.
The University of Michigan is consistently ranked among the top American public research universities, and Ann Arbor is routinely ranked as one of the best places to live in the U.S. due to its affordability, natural beauty, preservation of wooded areas, vibrant arts program, and lively downtown.
This position offers a highly competitive salary plus benefits. The initial appointment is for one year, with opportunity for extension based on performance, need, and availability of funds.
- Work with project team lead to develop, implement, and test the WRF-Hydro model across the Great lakes basin in alignment with requirements for the National Water Model and related research projects.
- Assist with transition of model parameters from a research to operations environment.
- Post-process hydrologic data and conduct analysis to assess streamflow and other hydrologic states.
- Work on a high-performance computing (HPC) environment executing the WRF-Hydro model.
- A bachelor or master degree in the natural sciences or engineering, with 1-3 years of related experience in hydrological science and modeling in research project and/or professional activities.
- Experience running hydrological models in a high-performance computing environment.
- Previous experience in processing large datasets in a variety of different data formats (ASCII, GRIB, or NetCDF).
- Graduate degree with some experience working in a research environment.
- Skill in working with radar, surface meteorological station, and/or numerical weather prediction data.
- Preference will be given to candidates that have experience with WRF-Hydro.
- Preference will also be given to candidates with a demonstrated ability to analyze hydrological model output.
- Experience with handling data in a linux/unix high-performance computing environment and scripting data analysis software such as R or Python is desired.
SEAS is committed to creating and maintaining an inclusive and equitable environment that respects diverse experiences, promotes generous listening and communications, and discourages and restoratively respond to acts of discrimination, harassment, or injustice. Our commitment to diversity, equity and inclusion is deeply rooted in our values for a sustainable and just society.
- To apply, applicants should prepare the following materials in a single PDF:
- Cover letter describing your qualifications related to the position and research accomplishments
- Curriculum vitae
- Contact information for three professional references
U-M EEO/AA Statement
The University of Michigan is an equal opportunity/affirmative action employer.