Job Openings

Research Scientist in Biophysical Modeling

CIGLR is seeking a full-time Research Scientist in Biophysical Modeling in collaboration with the National Oceanic and Atmospheric Administration (NOAA) Great Lakes Environmental Research Laboratory (GLERL) and the School for Environment and Sustainability (SEAS). This position can be filled at the Assistant, Associate, or full Research Scientist rank depending on experience.

You will lead CIGLR’s portfolio of research in biophysical modeling, especially the use of coupled numeric hydrodynamic and ecological models to understand large-scale patterns and develop forecasts for the Great Lakes. Our past research in this area has included a Lake Erie harmful algal bloom forecast (now operational with NOAA), a Lake Erie hypoxia forecast (transitioning to operations), and biophysical forecast models used in support of lake management and international science initiatives. These models are increasingly important for informing adaptive management of the lakes, providing early warning to coastal communities, and assimilating data from observing systems and other sources.

This position complements CIGLR’s ecological and biogeochemical research. Modeling approaches are incorporated into our science enterprise and are a key component of our process of research to operations, which involves hypothesis generation, fundamental science on mechanisms and interactions, model design, model parameterization, skill assessment, and translation to an information product. Our coupled ecological-physical models build on observational and experimental work and incorporate scale and heterogeneity beyond what can be accomplished by monitoring or experimentation. This is of utmost importance for research that will inform management of the lakes, such as the Great Lakes Water Quality Agreement.

Specific areas of interest include, but are not limited to, the following:

    • Forecasting effects of nutrients, meteorology, and hydrodynamics on water quality in the Great Lakes
    • Modeling impacts of climate change, invasive species, and land use change on ecosystem function and services in the Great Lakes over mid- to long-term timescales
    • Assimilating data from observing systems, remote sensing, traditional sampling, and ‘omics to inform forecasts and/or models for inference
    • Integration of lake biophysical models with regional climate models, landscape and watershed models, and Earth system models
    • Co-development of information products to meet needs of identified stakeholders (e.g., public water systems, recreation users, lake managers)

Qualifications
Candidates must have a PhD in oceanography, limnology, aquatic ecology, biogeochemistry, or a related field. The successful candidate is expected to have a strong record of publication, including first-author publications. Candidates should also have the following:

    • Experience developing hindcasts or forecasts using ecological or biogeochemical models coupled to 3-dimensional hydrodynamic models used in coastal marine or Great Lakes systems.
    • Experience with high performance computing systems and performing deterministic modeling in FORTRAN, Python, R, or similar programming language.
    • Ability to effectively collaborate with diverse experts at CIGLR, SEAS, GLERL, and other partner agencies/institutions/organizations.
    • Ability to effectively communicate, supervise and mentor employees and students, and provide scientific leadership of an interdisciplinary team.

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Earth System Modeler

CIGLR is seeking a candidate to join a team of modelers working on development, testing, and deployment of coupled, integrated earth system models of the Great Lakes basin. The purpose of this integrated earth system modeling effort is to support development of a real-time, three-dimensional circulation and flood forecast modeling system in the Great Lakes. The integrated earth system modeling components are designed to simulate physical processes including meteorology, hydrology, hydrodynamics, waves, and ice. Objectives of the project include calibration and verification of an unstructured three-dimensional baroclinic hydrodynamic lake model that includes the flood plains to predict coastal inundation. This lake model will be coupled to operational meteorological models such as the atmospheric High-Resolution Rapid Refresh model (HRRR), the WAVEWATCH III wave model, and the hydrologic National Water Model (NWM). You will work to explore, develop, and test coupling strategies between three dimensional hydrodynamic models and three-dimensional hydrologic models.

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

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 Limited: This is a one year appointment with the opportunity for extension based on performance, need, and availability of funds.

Responsibilities:

    • Work with the project team lead to develop, implement, execute and test coastal hydrodynamic and wave models in a high-performance computing (HPC) environment, including advanced model grid development for coastal inundation predictions.

    • Perform extensive model testing and validation, including post-processing hydrodynamic model data and conducting analysis to assess model skill against observations.

    • Develop and test model coupling infrastructure as part of an integrated earth system modeling approach.

    • Assist with transition of model parameters and configuration from research to operational environment. Document findings to internal and external audiences in reports, publications, and presentations.

Required Qualifications*

    • A bachelor’s degree in the natural sciences or engineering, with 1-3 years of related experience in hydrodynamic modeling in research projects and/or professional activities.

    • Experience configuring, running, and evaluating large scale earth system models in a high-performance computing environment.

    • Previous experience in processing large datasets in a variety of different data formats (ASCII, GRIB, or NetCDF).

    • Strong technical skills related to hydrodynamic, wave, or similar model development and high-performance computing.

    • US citizenship or permanent residency.

Desired Qualifications

    • Master’s or PhD in the natural sciences or engineering, with some experience working in a research environment.

    • Skill in working with surface meteorological stations, in-situ oceanographic observation, and/or numerical weather prediction data.

    • Experience in coupling earth system models.

    • Experience with FVCOM and/or WAVEWATCH III models.

    • Demonstrated ability to analyze hydrodynamic model output.

    • Experience with handling data in a Linux/Unix high-performance computing environment and scripting data analysis software such as R, Python, or IDL.

    • Experience working with geospatial data and developing hydrodynamic model grids.

Apply: The application deadline is March 31, 2023. 

 

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Earth System Modeler Postdoc

CIGLR is seeking a candidate to join a team of modelers working on development, testing, and deployment of coupled, integrated earth system models of the Great Lakes basin. The purpose of this integrated earth system modeling project is to support development of a real-time three-dimensional circulation and flood forecast modeling system in the Great Lakes. The integrated earth system modeling components are designed to simulate physical processes including meteorology, hydrology, hydrodynamics, waves, and ice. Objectives of the project include calibration and verification of an unstructured three-dimensional baroclinic hydrodynamic lake model that includes the flood plains to predict coastal inundation. This lake model will be coupled to operational meteorological models such as the atmospheric High-Resolution Rapid Refresh model (HRRR), the WAVEWATCH III wave model, and the hydrologic National Water Model (NWM). The candidate will work to explore, develop, and test coupling strategies between three-dimensional hydrodynamic models and three-dimensional hydrologic models. The ideal candidate will have strong technical skills related to hydrodynamic, wave, or similar model development and high-performance computing.

Responsibilities:

    • Work with the project team lead to develop, implement, and test hydrodynamic models. This includes advanced model grid development for coastal inundation predictions.

    • Conduct extensive model testing and validation, including skill assessment to evaluate model performance against observations.

    • Develop and test model coupling infrastructure as part of an integrated earth system modeling approach.

    • Assist with the transition of model parameters and configuration from research to operational environment.

    • Post-process hydrodynamic model data and conduct analysis to assess model skill.

    • Work in a high-performance computing (HPC) environment executing coastal hydrodynamic and wave models.

    • Document findings to internal and external audiences in reports, publications, and presentations.

Required Qualifications*

    • PhD in physical oceanography, atmospheric science, or similar field.

    • Experience configuring, running, and evaluating large scale earth system models in a high-performance computing environment.

    • Experience in processing large datasets in a variety of different data formats (ASCII, GRIB, or NetCDF).

    • Skill in working with data from surface meteorological stations, in-situ oceanographic observation, and/or numerical weather prediction.

    • Experience with handling data in a Linux/Unix high-performance computing environment and scripting data analysis software such as R, Python, or IDL.

    • Strong publication record in a relevant field, including at least one lead-author publication.

    • Strong communication skills and demonstrated ability to work independently in collaboration with an interdisciplinary team.

    • US citizenship or permanent residency required.

Desired Qualifications

    • Experience with FVCOM, ROMS, SCHISM and/or WAVEWATCH III models.

    • Experience in coupling hydrodynamic and hydrologic models (nearshore coupling).

    • Experience in coupling hydrodynamic and wave models.

    • Previous work on coastal inundation prediction.

    • Experience working with geospatial data and developing hydrodynamic model grids.

Apply: The application deadline is March 31, 2023. 

 

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Data Science Postdoc 

CIGLR is seeking outstanding candidates for a postdoctoral scholar position in data science. In collaboration with the National Oceanic and Atmospheric Administration (NOAA) Great Lakes Environmental Research Laboratory (GLERL) and School for Environment and Sustainability (SEAS), the successful candidate will lead research that utilizes data science to advance hydrometeorological prediction and water management decision support. The postdoctoral fellow will be part of a large interdisciplinary team at GLERL, CIGLR, and SEAS that is developing the next generation prediction system for determining the mean and extreme water levels. This new system will provide the foundation for defining the risk of coastal inundation impacts across subseasonal to annual time scales for the Laurentian Great Lakes.

Specifically, the postdoctoral fellow will utilize data-driven approaches to optimize the design of a next generation water level prediction system for subseasonal to annual predictions. Approaches will leverage the latest advancements in hydrometeorological data; modeling of meteorology, climate, and hydrology; and forecasting to characterize hydrometeorological variability across space-time scales, identify sources of uncertainty, and improve predictability of water supply and water levels. Work will be conducted as part of an interdisciplinary team bringing together expertise in meteorology and climate, hydrology, water management, and stakeholder engagement.

This person will spend their on-site work time at the NOAA Great Lakes Environmental Research Laboratory in Ann Arbor, Michigan. Hybrid and flexible work agreements may be made to allow for partial off-site work. 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:

    • Develop optimized methodology to blend hydroclimate datasets as inputs to the next generation water level prediction system.

    • Investigate source of uncertainties and predictability of net basin supply components using data-driven approaches.

    • Lead at least one manuscript based on research findings for submission to a peer-reviewed journal, present results at a conference(s).

    • Contribute to the co-development of a next generation water supply and water level forecast for the Great Lakes through participation in stakeholder engagement activities and close collaboration with the project team.

    • Attend regular project meetings at GLERL, CIGLR and SEAS, as well as inter-agency group meetings to report progress.

Required Qualifications*

    • PhD in hydroinformatics, statistics, mathematics, water resources engineering, or similar field.

    • Demonstrated ability to conduct data-driven hydroclimate research using gridded atmospheric, land-surface, and/or hydrological model outputs for subseasonal, seasonal, and/or annual prediction time scales. Example approaches include use of stochastic methods, statistical modeling, and artificial intelligence (e.g., time series analysis, machine learning, deep learning, random forest ensemble learning, spatiotemporal data analysis). Experience with analyses to evaluate sources of uncertainty and/or predictability are particularly preferred.

    • Experience working on gridded outputs from climate, atmospheric, and hydrological models, including netCDF, grib2, and HDF5 storage formats.

    • Strong publication record in the relevant field, including at least one lead-author publication.

    • Strong communication skills and demonstrated ability to work independently in collaboration with an interdisciplinary team.

    • Proficiency with handling various data formats, such as NetCDF, GRIB2, ASCII, and shapefiles. This includes visualization, geospatial data analyses, and dealing with map projections using existing libraries for programming languages such as Python, R, and Matlab.

    • Proficiency with working on a supercomputer or a cluster computing environment. This includes shell scripting, batch job submissions, and data transfer.

Desired Qualifications

    • Exposure to atmospheric and hydrological science, such as research that characterizes hydroclimatic variability across space-time scales.

    • Understanding of global circulations, teleconnection patterns, and their impacts on regional climate (e.g., precipitation patterns).

    • Experience using Great Lakes regional hydrological/climate datasets (e.g., Regional Deterministic Reanalysis System, the Canadian Precipitation Analysis system).

Apply: The application deadline is April 30, 2023. 

 

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Student Fellowships

CIGLR offers two fellowship programs that support student research opportunities, in order to train the next generation of Great Lakes researchers. Click the button to learn more about current and upcoming student fellowship opportunities.

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