Job Openings

Postdoc Fellowship: Atmospheric Science

The Cooperative Institute for Great Lakes Research (CIGLR) is seeking outstanding candidates for a postdoctoral scholar position in atmospheric 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 in atmospheric science, regional climate variability, understanding and predicting hydrometeorology within regional domains. 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 in the Great Lakes. This new system will provide the foundation for defining risk of coastal inundation impacts across subseasonal to annual time scales for the Laurentian Great Lakes.

Specifically, the postdoctoral fellow will evaluate existing hydrometeorological datasets as inputs to the next generation water level prediction system, characterize hydrometeorological variability across space-time scales, and develop modeling approaches to advance hydrometeorological prediction for a target domain using statistical, process-oriented, and hybrid methods. Work will be conducted as part of an interdisciplinary team bringing together expertise in meteorology and climate, hydrology, water management, and stakeholder engagement.

Required Qualifications

    • PhD in meteorology, atmospheric science, climatology, or similar field (e.g., hydrometeorology and hydroclimatology).
    • Demonstrated ability to work with gridded atmospheric model outputs using statistical, data-driven analysis techniques and/or process-oriented analyses that support physical relations indicated by statistical analyses. Example datasets include the data from models participating in the North American Multi-Model Ensemble (NMME), the Subseasonal Experiment (SubX), and the Coupled Model Intercomparison Project (CMIP).
    • 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

    • Experience with model intercomparison across different types of modeling (e.g., lumped, conceptual models, physics-based models, statistical models).
    • Experience performing analyses targeted to subseasonal, seasonal, and/or annual time scales.
    • Understanding of global circulations, teleconnection patterns, and their impacts on regional climate (e.g., precipitation patterns).
    • Familiarity with various parameterization schemes utilized in atmospheric modeling.
    • Experience using Great Lakes regional hydrological/climate datasets (e.g., Regional Deterministic Reanalysis System, the Canadian Precipitation Analysis system).

The application deadline is December 21, 2022.

 

Postdoc Fellowship: Data Science

The Cooperative Institute for Great Lakes Research (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.

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).

The application deadline is December 21, 2022.

 

Postdoc Fellowship: Dynamic Energy Budget Modeling of Dreissenid Mussels in the Great Lakes

A postdoctoral fellowship is available for a highly qualified individual to join the Cooperative Institute for Great Lakes Research (CIGLR, https://ciglr.seas.umich.edu/). 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 successful candidate will work with a multidisciplinary team at CIGLR and the NOAA Great Lakes Environmental Research Laboratory (GLERL) to improve models of how invasive dreissenid mussels shape the lakes’ food webs. In particular, the candidate will develop a dynamic energy budget model for Dreissena that predicts net growth of mussels, including changes in energy storage, structural tissues, maturation, reproduction, and nutrient cycling. This model will build upon a rich history of studies conducted at CIGLR, GLERL and elsewhere related to mussel feeding and excretion, population dynamics, growth, and size structure. In addition to model development, the candidate will assist with planning and overseeing experiments required to parameterize the model.

Required Qualifications

    • A Ph.D. in natural sciences or engineering with research experience in limnology, ecological modeling, or a similar field
    • A strong background in deterministic modeling
    • Familiarity with data analysis and visualization in a scripting environment using R, Python, or similar software
    • Demonstrated ability to lead the development of manuscripts for refereed journal publication
    • Strong communication skills and a demonstrated ability to work both as a team and independently

Desired Qualifications

    • Experience with dynamic energy budget models, or similar bioenergetic models
    • Experience with developing parameter estimates from experiments or existing sources
    • Experience conducting experiments with live organisms
    • Demonstrated ability to analyze data, quantify uncertainty, and publish results in a timely manner

The application deadline is January 2, 2023.

 

Biogeochemistry Laboratory Analyst (2 positions)

The Cooperative Institute for Great Lakes Research (CIGLR) is seeking two (2) candidates to join our research team to work on harmful algal blooms, hypoxia, and invasive species in the Great Lakes. You will be responsible for performing laboratory analyses related to aquatic biogeochemistry in the Great Lakes and their watersheds.

Required Qualifications

    • Bachelor’s  degree in environmental science or related field
    • Upper-level coursework in analytical chemistry or related to surface water chemistry
    • Professional or academic experience working in a laboratory with at least one year of experience performing analytical chemistry related to water quality or biogeochemistry
    • Experience working independently on problem-solving and balancing demands of multiple projects
    • Familiarity with data management and analysis using products such as Excel, R, MATLAB, Python, or similar platforms

Desired Qualifications

    • Two (2) or more years of professional or graduate experience working in a laboratory
    • Demonstrated experience developing, adapting, or troubleshooting analytical methods for biogeochemistry or water quality

The application deadline is January 3, 2023.

 

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.