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Corteva Agriscience is seeking a highly motivated 6-month intern to join our Research and Development team. This role sits at the intersection of meteorological field sensing, the Internet of Things (IoT), and digital agriculture. The successful candidate will evaluate the integrity of environmental data streams and explore how advanced weather networks and novel sensing technologies impact plant breeding, crop health, and predictive modeling. This position offers a unique opportunity to work with cutting-edge hardware—including weather stations, UAVs, and robotic platforms—while performing complex computational tasks to ensure high-fidelity data is available for downstream agronomic products.
Job Responsibility:
Develop and implement automated quality control (QC) scripts using Python or R to identify sensor drift, outliers, and transmission gaps
Analyze and organize large, complex datasets to extract actionable insights for crop modeling
Investigate existing weather networks to ensure consistency and reliability across field sites
Utilize GIS and remote sensing tools to analyze the spatial representativeness of station siting
Troubleshoot, calibrate, and maintain field sensing equipment
Contribute to the design, engineering, and testing of new sensor prototypes and IoT devices
Conduct field visits for equipment inspection and data collection
Potential to operate UAVs and/or robots and their associated payloads to support phenotyping operations
Design and execute a dedicated research project focused on sensor performance, network optimization, or technology impact, culminating in a presentation to R&D leadership and station staff
Work alongside researchers across various disciplines (Atmospheric Science, Plant Breeding, Engineering) to communicate how data quality and novel technologies influence future farming operations
Requirements:
Priority given to current seniors or graduate students (Master’s or PhD) at an accredited university or community college
Majors in Meteorology, Atmospheric Science, Geospatial Information Science (GIS), Environmental Engineering, Agronomy, or related STEM fields are preferred
Proficiency in Python or R is required, specifically for data manipulation, statistical analysis, and script automation
Strong understanding of GIS principles and geospatial software (ArcGIS, QGIS, or Google Earth Engine)
Demonstrated ability to troubleshoot, build, or test sensitive environmental sensors or electronic equipment
Proven ability to clean and organize complex datasets
Strong problem-solving skills
Ability to work effectively in both office settings and outdoor field environments
Proficiency in Microsoft Office Suite
Willingness to work in a variety of environments, including both office-based computational work and outdoor field sites
Ability to take occasional day trips to off-site research locations
Nice to have:
Experience with remote sensing and the application of technology to plant screening techniques is a plus
Experience with station calibration and maintenance is highly valued