Available DAWN Internships

University of Minnesota (Twin Cities, MN)
Project Focus: Establish Proactive Extension to Engage Stakeholders for Coproduction

University of Minnesota (Twin Cities, MN)
Project Focus: Establish Proactive Extension to Engage Stakeholders for Coproduction

University of Nebraska (Lincoln, NE)
Project Focus: Build the DAWN Science Modeling and Decision Support System

University of Nebraska (Lincoln, NE)
Project Focus: Establish Proactive Extension to Engage Stakeholders for Coproduction

University of Nebraska (Lincoln, NE)
Project Focus: Build the DAWN Science Modeling and Decision Support System

University of Maryland (College Park, MD)
Project Focus: Build the DAWN Science Modeling and Decision Support System

University of Maryland (College Park, MD)
Project Focus: Develop DAWN Decision Support Predictions

Position Description (Virtual/In-person): The goal of DAWN is to build a decision-support system that helps to increase land, nutrient, and water use efficiency in order to maximize crop production in corn, soy, and bioenergy fields. A core aspect of the project is to support social science research related to extension and engagement. The goal of this project is to support stakeholder engagement to improve the design, refinements, and support the use of DAWN to improve water and nutrient management decisions on-farm. Wide-reaching communications strategies are one impactful approach to sharing about DAWN to different audiences in the US Corn Belt. https://dawn.umd.edu

The student intern will work with Dr. Kenney, the DAWN communications specialist, and the extension team on impact-oriented communications. Duties will include helping to draft updates/news releases, social media posts, 2-page fact sheets, student blog posts, or other emerging communication priorities. The work requires strong written communication skills and attending multiple virtual (and potentially in-person) meetings to learn and communicate about different DAWN activities.

About the Lab: This position will be hosted at the Institute on the Environment at the University of Minnesota - Twin Cities on the Saint Paul campus. The intern will work in a space alongside other staff members and post-docs who are conducting research that helps the planet and people prosper together. The intern will be supervised by Ashley Humphrey, who is the communications specialist for research projects, and mentored by Melissa Kenny, the director of research initiatives at the Institute. There will be in-person expectations as well as remote work opportunities.

Position Description (In-person prefered): The goal of DAWN is to build a decision-support system that helps to increase land, nutrient, and water use efficiency in order to maximize crop production in corn, soy, and bioenergy fields. A core aspect of the project is to support social science research related to extension and engagement. The goal of this project is to support stakeholder engagement to improve the design, refinements, and support the use of DAWN to improve water and nutrient management decisions on-farm. https://dawn.umd.edu

The student intern will work with Dr. Kenney and the Extension team on stakeholder-engaged research. Duties will include research tasks such as helping to set up and pilot focus groups and surveys; supporting the coordination of end-user interviews to assess DAWN’s usability; assisting with qualitative data analysis; and conducting literature reviews for the Extension team. The work will include attending multiple virtual (and potentially in-person) meetings with the research and extension teams, as well as supporting the technical facilitation of stakeholder meetings.

About the Lab: The Environmental Decision Support Science group is housed at the University of Minnesota's Institute on the Environment led by Dr. Melissa Kenney. We conduct multi-disciplinary social science research at the intersection of the environment, technology, and society. Strategies and decisions made at this nexus often encounter significant uncertainty about scientific evidence and involve stakeholders with conflicting objectives and values. The goal of our team is to understand and improve the processes and tools that aid these decisions, both in the public and private sectors. https://z.umn.edu/melissakenney The communications intern would also be part of the Institute on the Environment communications team, which focuses on impactful storytelling to drive societal change. http://environment.umn.edu/.

Position Description (In-person preferred):  The innovative fertilizer research project (NRATE) is a multidisciplinary collaboration at UNL that focus on Advanced N management, enhanced efficiency fertilizers, conservation practices (cover crops), nitrogen and carbon emissions, soil health, soil microbial, nitrogen leaching and water quality, plant health, climate, and crop modeling and economic analysis.

The intern will assist with research data collection (soil samples, georeferenced crop scouting, tissue sampling), data processing, and visualization for the NRATE Project. The candidate will closely work with graduate students, technicians, and other interns to achieve team goals regarding data collection and analysis. Skills required are good written and oral communication and basic familiarity with data science and visualization principles. Responsibilities based on skills and desired experiences of the intern.

About the Lab: Digital Farming Lab: Led By Dr. Guillermo Balboa. Our research focuses on nutrient management and precision agriculture and includes site-specific crop management, cropping systems and simulation models, integrated digital agriculture technologies and crop ecophysiology. https://agronomy.unl.edu/digital-farming-lab/

Position Description (In-person preferred): On-farm research can provide a great avenue to accelerate learning about topics that impact farm productivity and profitability. It is research conducted on farmer fields, using farmer equipment, and with farmer production practices. This means the research is directly applicable to their operation. The Nebraska On-Farm Research Network approaches topics that are critical to farmer productivity, profitability, and sustainability. These topics include nutrient management, pest control, irrigation strategies, conservation programs, new technologies, soil amendments, cultural practices, and hybrid and variety selection. Research comparisons are identified and designed to answer producers’ production questions. Projects’ protocols are developed first and foremost to meet individual cooperator needs. This network is an excellent environment to test the DAWN Tool.

The intern will be assisting with research data collection (soil samples, georeferenced crop scouting, tissue sampling, aerial imagery acquisition) for existing on-farm research studies (anticipate approximately 120 studies, of which nearly 50 will be related to nitrogen management). Depending on skills and background, can assist with data processing and analysis. Contribute to extension outcomes such as: 1) Film and produce short video updates of research studies and Users testing the DAWN Tools; 2) Assist in the development of articles for CropWatch and the Nebraska On-Farm Research Network newsletter

About the Lab: Our research focuses on soil fertility and precision agriculture and includes site-specific crop management, cropping systems and simulation models, integrated digital agriculture technologies and crop ecophysiology. https://agronomy.unl.edu/digital-farming-lab/

Position Description (In-person preferred): The summer intern will work on testing the Spatial EvapoTranspiration Modeling Interface (SETMI) model in the DAWN DSS by supporting farmer collaborators, helping them understand the model and conduct irrigation scheduling of their irrigated fields during the 2025 growing season. This will involve the use of satellite imagery and climate data to run the model.

The interns will interface with farmers, helping them run the DAWN DSS and the different tools while obtaining feedback useful for the project.  They will follow the progress of the DAWN DSS recommendations and collect data and results They will also help prepare a report at the end of the season.  

About the Lab: The position will be hosted at the Daugherty Water for Food Global Institute at the University of Nebraska, at the Nebraska Innovation Campus in Lincoln, NE. https://waterforfood.nebraska.edu/. The intern will have access to computers and University of Nebraska-Lincoln facilities.

Position Description (In-person preferred): Agricultural producers are navigating increasingly complex decisions as they produce food and energy crops while facing increasing climate anomalies, economic pressures, and environmental concerns. Routine decisions such as crop choice, fertilizer use, irrigation scheduling, and reservoir operations have wide-ranging impacts on water availability, nutrient loss, agricultural production and agrohydrosystem sustainability at local to national scales. Predicting these complicated cross-sectoral interactions requires complex coupled Earth system models, cutting-edge technologies, and significant computational resources. Given the computational hurdles in running coupled models to provide timely information at decision-relevant scales, there is a pressing demand for efficient predictive tools that can bolster field-scale agricultural and water decisions through a comprehensive systems approach. Machine learning and artificial intelligence technologies offer a validated approach to develop these cost-effective tools.

The student interns will work with members of Dr. Liang’s Lab at UMD/ESSIC to develop machine learning models that use observations and climate model outputs to predict agricultural outcomes such as crop growth and yields. Interns will also have the opportunity to develop manuscripts that report their modeling results. Candidates should have some coding experience and an interest in applying machine learning techniques to analyze large data sets.

About the Lab: The Earth System Science Interdisciplinary Center (ESSIC) is a joint center between the UMD Departments of Atmospheric and Oceanic Science, Geology, and Geographical Sciences. ESSIC faculty primarily conduct research on topics related to climate variability, atmospheric composition, and the global carbon and water cycles. Dr. Liang’s Earth System Model Research & Development (EaSM) Lab uses integrated global and regional models, alongside machine learning/artificial intelligence technologies, to study climate dynamics, seasonal climate and hydrology predictions, climate change projections, and associated environmental and agricultural consequences. Lab members include undergraduates, graduate students, and postdocs who work together in a supportive and collaborative environment.

Position Description (In-person preferred): Agricultural producers are navigating increasingly complex decisions as they produce food and energy crops while facing increasing climate anomalies, economic pressures, and environmental concerns. Routine decisions such as crop choice, fertilizer use, irrigation scheduling, and reservoir operations have wide-ranging impacts on water availability, nutrient loss, agricultural production and agrohydrosystem sustainability at local to national scales. Predicting these complicated cross-sectoral interactions requires complex coupled Earth system models, cutting-edge technologies, and significant computational resources. Given the computational hurdles in running coupled models to provide timely information at decision-relevant scales, there is a pressing demand for efficient predictive tools that can bolster field-scale agricultural and water decisions through a comprehensive systems approach. Machine learning and artificial intelligence technologies offer a validated approach to develop these cost-effective tools.

The student interns will work with members of Dr. Liang’s Lab at UMD/ESSIC to develop machine learning models that use observations and climate model outputs to improve subseasonal-to-seasonal climate predictions for agricultural decision support. Interns will also have the opportunity to develop manuscripts that report their modeling results. Candidates should have some coding experience and an interest in applying machine learning techniques to analyze large data sets.

About the Lab: The Earth System Science Interdisciplinary Center (ESSIC) is a joint center between the UMD Departments of Atmospheric and Oceanic Science, Geology, and Geographical Sciences. ESSIC faculty primarily conduct research on topics related to climate variability, atmospheric composition, and the global carbon and water cycles. Dr. Liang’s Earth System Model Research & Development (EaSM) Lab uses integrated global and regional models, alongside machine learning/artificial intelligence technologies, to study climate dynamics, seasonal climate and hydrology predictions, climate change projections, and associated environmental and agricultural consequences. Lab members include undergraduates, graduate students, and postdocs who work together in a supportive and collaborative environment.