IonE Postdoctoral Fellows use system thinking and deploy a range of interdisciplinary methods to answer critical questions. We have grouped the IonE Postdoctoral Fellow projects for this year under two groupings of broad interdisciplinary methods: 1) social science and synthesis and 2) systems modeling and data science.
Each project description includes a video overview to introduce you to the project and let you hear directly from the PI.
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A. Improving Decision Support Products to Improve Environmental Decisions
Working with IonE’s Environmental Decision Support Science team led by PI Kenney and a team of postdocs and research staff, along with NOAA and partners across the U.S. you will be part of multiple projects that are proposed that aim to improve the use of scientific information in a range of nationally important decisions related to floods, droughts, weather hazards, environmental changes, and other extreme events. This research will engage with decision support users, refine diagnostic tools, and conduct research on visualizations and user-controlled decision support systems to increase the ability of individuals and communities to use these data products for early warning actions and longer-term resilience planning decisions. The team includes diverse interdisciplinary backgrounds; knowledge of qualitative and/or quantitative social science methods is required. Community engaged-scholarship or AI skills to support user identification and priorities are a plus.
PI: Melissa Kenney
Video overview (recorded 2025) updated video coming soon
C. Adaptation in the Natural Resources Sector
Working with the Midwest Climate Adaptation Science Center and the US Geological Survey, collaborate on projects focused on climate change in ecosystems, the design of strategies to reduce those impacts, and synthesis research on adaptation that spans the Midwest region. Requires collaboration with natural resource practitioners or managers and interaction with USGS researchers (in residence at the IonE).
PI: Jessica Hellmann
Video overview (recorded 2025)
E. Midwest Carbon Reduction focused on Public / Private Partnerships
You will conduct translational science and enable collaborative projects between university researchers and external organizations via the Midwest Carbon Leadership Project (MW CLP). The MW CLP is a platform for collaboration between industry and academia to address critical knowledge barriers related to deep decarbonization. It includes a recurring conference (next one: Feb 2025) and on-going working groups that are supported by the postdoctoral researcher. Diverse disciplinary background welcome; experience or interest in the use of diverse social science methodologies, science communication, and project coordination is particularly desirable. Specific research topic TBD and determined in consultation with MW CLP participants / working group members.
PIs: Jessica Hellmann & PI: Melissa Kenney
F. Assessment of Just and Equitable Energy Transition Pathways
You will conduct synthesis and translational science to reduce carbon reduction as part of IonE’s energy transition research portfolio conducted with community organizations. Topical expertise in relevant energy topics is required. Diverse disciplinary background welcome; experience or interest in social science, policy analysis, and/or clean energy futures is particularly desirable.
PIs: Jessica Hellmann & Melissa Kenney
L. Crop Type Mapping
Higher resolution satellite data has become more freely available. You will add to efforts currently underway around the world in crop type mapping using satellite remote sensing techniques in our team to complement those efforts. Numerous approaches can be used and we will also collaborate with research teams who have already made significant progress. The goal of this project is to increase high-resolution global crop type map completeness, with specific location and crop-specific studies, while leveraging existing products such as CDL of USDA wherever possible. Therefore demonstrable past experience in using remote sensing data in mapping crop types is essential for success. Interest or past work in global agriculture and food security is a plus. Part of the research time will also be devoted to analyzing world food security related questions depending on interests and expertise.
PI: Deepak Ray
M. Crop Nutrient Mapping and Analysis
Underapplication of fertilizers is a major concern in various countries whereas in other countries over-application is a major concern. At present research and policies are being developed using limited, often out-of-date crop-specific nutrient information, that are spatially not high-resolution, to identify solutions. Consequently, timely crop-specific nutrient budgets and/or trends in application, and developing comprehensive responsible plant nutrient use planning, though highly sought after, suffers. Foundational comprehensive fertilizer and manure use by crops time series dataset is urgently needed to remedy the situation. In this project we will further build and update new global gridded fertilizer and manure application rates per crop datasets and use them to support sustainable agriculture productivity growth analysis, contributing to a world free of hunger but within planetary boundaries.
PI: Deepak Ray
N. Modeling Diverse Clean Energy Solutions for Minnesota
You will use data science and systems modeling methods to explore the effectiveness of different carbon reduction pathways as part of IonE’s energy transition research portfolio conducted with community organizations. Topical expertise in relevant energy topics is required. Diverse disciplinary background welcome; experience or interest in systems modeling research on renewable energy pathways is particularly desirable.
PIs: Jessica Hellmann, Nat Springer, and Melissa Kenney
O. Sustainable Supply Chains in the Food System
Working with our Food System Supply-chain Sustainability (FoodS^3) team of research scientists and postdocs, along with project partners (companies, industry groups, and NGOs) you would help us enhance the underlying data and optimization of our FoodS^3 platform. The successful candidate will have strong scientific coding and data science skills with experience collating and synthesizing disparate sets of data. This may include one or more of the following:
Developing an enhanced FoodS^3 model to include circular feedback effects, prices, and emission factors
Constructing scenarios that illustrate the usefulness of the enhanced model and provide actionable knowledge to key project partners and stakeholder
Building out additional crops, animals, facilities, and impact categories to the existing FoodS^3 portfolio
Exploring global agricultural commodity bilateral trade data integration
Applying life-cycle assessment to improve and downscale FoodS^3 emissions factors
Developing and streamlining the code for the FoodS^3 platform
Alignment with other leading agricultural assessment tools and models
Some combination of knowledge and experience in systems analysis, environmental impact assessment, data science skills (Python/R, optimization modeling, high-performance computing), material flow analysis, and/or agricultural footprinting required. Other computer science, software engineering, biophysical modeling, or supply chain management skills are a plus.
PI: Jennifer Schmitt & Nat Springer
P. Modeling Nutrition-Based Animal Diets in the Food System
A joint position between IonE and the Department of Animal Science, this post-doc will work with our Food System Supply-chain Sustainability (FoodS^3) team of research scientists and postdocs, along with project partners (companies, industry groups, and NGOs) to build out a new FoodS^3 nutrition-based model and database. This new approach will form the basis for an enhanced FoodS^3 platform to model the feedback loops and circularity inherent and fundamental to U.S. crop and livestock systems, with a particular focus on carbon, nitrogen, and phosphorus flows and circularity. This may include developing data on key nutritional components of FoodS^3 crops and feed ingredients that drive feed formulations and adapting animal industry nutrient requirement models to optimize species specific feeding. Some combination of knowledge and experience in animal specific nutrition-based modeling (cattle, hogs, broilers), substance flow analysis, and data science skills (Python/R, optimization modeling) are required. Other computer science, software engineering, biophysical modeling, or supply chain management skills are a plus.
PIs: Nat Springer, Jennifer Schmitt, Pedro Urriola, and Jerry Shruson
Emergent project opportunities may arise. We will add these to the project list over the course of the application period.