Biophysical Modeling Analyst

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 include:

• Your specific interest in the position and experience that is directly related to this position.
• A detailed description of experience that pertains to each of the required qualifications listed below. .
• To be considered for the intermediate level, a detailed description of experience working with mechanistic ecosystems and/or hydrodynamic models.

Summary

We are seeking an individual to join our ecological and physical modeling teams at the University of Michigan's Cooperative Institute for Great Lakes Research (CIGLR) and the National Oceanic and Atmospheric Administration's Great Lakes Environmental Research Lab (NOAA GLERL). Under the direction of project principal investigators, the Biophysical Modeling Analyst will work collaboratively with CIGLR and NOAA GLERL scientists to:

• Develop experimental ecological forecasts linked to the hydrodynamic models of the Great Lakes Operational Forecast System.
  
• Evaluate model performance through statistical comparison of modeled and observed water quality, biological, and physical variables. These models simulate ecological and limnological processes within the Great Lakes including water quality, harmful algal blooms, and biogeochemical processes, among others.

This position can be filled at the Research Laboratory Specialist Associate or Intermediate level depending on experience.

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.

Term Appointment: This is a one-year term appointment with the possibility of renewal.

Mission Statement

The School for Environment and Sustainability (https://seas.umich.edu/) is a collaborative and interdisciplinary school. Our mission includes contributing to the protection of environmental resources and the achievement of a sustainable society. We accomplish this by generating and sharing knowledge, contributing to policy and engaging managers and stakeholders. The University of Michigan is a top-ranked public university with excellence in research and teaching. Ann Arbor, home to the University of Michigan, is a town known for arts, culture, parks and restaurants.

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 responds 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.

Who We Are

Your appointment 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 press problems facing the Great Lakes region.

Responsibilities*

These responsibilities may vary depending on the level the candidate is hired into.

• Assist with or run numerical hydrodynamic, ecological, and biophysical models of the Great Lakes (e.g., models linked to the Finite Volume Community Ocean Model (FVCOM) using a high-performance computing system. This may also include some model adaptation, revision, and development.
• Process, analyze, and visualize empirical ecological and oceanographic datasets to inform model development and advance understanding of the biogeochemistry and ecology of the Great Lakes.
• Evaluate the performance and skill of ecological and hydrodynamic models of the Great Lakes by statistical comparison of modeled versus observed water quality, biological, and physical variables in a programming environment (e.g., R or Python).
• Present data findings to the project team and contribute to publications by helping to write manuscripts, analyze data, and prepare figures.

Required Qualifications*

• A bachelor's degree in the natural sciences, engineering, or related field. A master's degree is preferred.
• At least one (1) year professional or academic experience processing, analyzing, and visualizing ecological and/or oceanographic datasets.
• Experience working with coupled hydrodynamic and ecological models for lakes or oceans is preferred.
• Experience using programming languages (e.g., R or Python) to perform data manipulation, execute statistical analyses, and generate figures, including geographical data.
• Experience in an academic research and/or professional setting working with code and/or output for geophysical fluid dynamic (lake, ocean, atmosphere) or aquatic ecological models.
• Familiarity with hydrodynamic/ocean modeling frameworks such as FVCOM is preferred.
• Experience recording scholarly productivity commensurate with career stage, including co-authorship on peer-reviewed manuscripts is preferred.
• Experience running mechanistic ecological models using a high-performance computing system is preferred.

Work Locations

The selected candidate will spend the majority of their time at NOAA's Great Lakes Environmental Research Lab (GLERL)and will collaborate with colleagues at CIGLR, GLERL, SEAS and other Great Lakes partners.

Remote and flexible work agreements may be made to support partial off-site work at a remote location..

Additional Information

Salary will be determined based on experience and level.

Application Deadline

Job openings are posted for a minimum of seven calendar days. This job may be removed from posting boards and filled any time after the minimum posting period has ended.

Applications will be reviewed as received throughout the posting period and continue until the position is filled.

U-M EEO/AA Statement

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