Join Vylor—Powering the Future of Agriculture
At Vylor, we’re advancing agriculture through breakthrough science—combining elite germplasm, cutting-edge biotech, and next-generation expertise in gene editing and molecular breeding. Our portfolio includes trusted industry brands like Pioneer®, Brevant®, and Hoegemeyer®, delivering performance farmers rely on.
Join us to help scale innovation globally and shape what’s next in crop science.
Vylor is seeking a highly motivated 6-month R&D Environmental Sensing, UAV & Data Analytics Intern to join our team at the Johnston, Iowa Global Campus. This role sits at the intersection of environmental physics, unmanned aerial systems (UAS), Internet of Things (IoT) technologies, and data science. The position provides a unique, hands-on opportunity to evaluate cutting-edge environmental data streams, operate advanced remote sensing payloads, and explore how novel field sensors impact plant breeding, crop health, and predictive crop modeling.
The successful candidate will work in both laboratory and field environments, deploying advanced sensors and developing data pipelines to ensure high-fidelity environmental data is available for downstream agronomic modeling.
Key Responsibilities
- UAV & Thermal Remote Sensing Operations: Plan, coordinate, and execute UAV flights to capture high-resolution thermal and multispectral imagery. Manage the end-to-end photogrammetric and thermal calibration processing workflows to translate raw aerial imagery into actionable crop water-use and stress analytics.
- Novel Soil Moisture & Environmental Sensor Evaluation: Help investigate, deploy, and benchmark next-generation soil moisture sensing technologies, exploring novel methods such as cosmic ray neutron sensing (CRNS), ground- or satellite-based radar, and IoT-enabled environmental probes.
- Data Quality Control & Pipeline Automation: Develop and implement automated data quality control (QC) scripts using Python or R to ingest raw sensor data, identify sensor drift, flag outliers, and handle transmission gaps across various field sites.
- Hardware Troubleshooting & Calibration: Assemble, calibrate, test, and troubleshoot field-sensing equipment and environmental stations. Optimize station siting, evaluate sensor performance, and perform routine maintenance to ensure data integrity.
- Geospatial & Statistical Analysis: Utilize GIS and remote sensing tools (e.g., QGIS, ArcGIS, or Google Earth Engine) to analyze the spatial representativeness of weather stations and integrate geospatial layers with in-field meteorological observations.
- Cross-Disciplinary Collaboration: Partner with breeders, agronomists, data scientists, and crop modelers to communicate how environmental data quality and spatial variability impact downstream predictive models.
- Dedicated Research Project: Design, execute, and present a dedicated research project focused on UAV thermal imaging analytics or soil moisture sensor network optimization to Vylor R&D leadership.
- Field & Office Flexibility: Willingness to work in a hybrid office/field environment, including occasional day trips to off-site research locations for equipment inspection, deployment, and UAV flight campaigns.
Qualifications
Required Education & Background
- Education: Currently enrolled as a senior undergraduate, Master's, or PhD student at an accredited university or community college.
- Target Majors: Meteorology, Atmospheric Science, Geospatial Information Science (GIS), Agricultural/Biological Engineering, Environmental Science, Geophysics, or related STEM fields with a strong interest in environmental sensing.
Technical Skills & Experience
- Programming Proficiency: Basic to intermediate proficiency in Python or R, specifically for data manipulation, geospatial processing, and statistical analysis (e.g., Pandas, NumPy, Rasterio, GDAL, or Tidyverse).
- Geospatial & Remote Sensing Expertise: Strong fundamental understanding of GIS, coordinate reference systems, and remote sensing principles (specifically thermal infrared radiometry or electromagnetic wave interaction with soil/canopy).
- Data Management: Demonstrated ability to organize, clean, and analyze large, complex, or unstructured environmental datasets.
- Hardware & Field Capability: Hands-on experience with field equipment, electronics, or environmental sensors. Demonstrated ability to troubleshoot hardware/sensor connectivity or calibration issues.
- Soft Skills: A passion to explore, question, and propose innovative solutions to technical challenges; ability to adapt quickly in a fast-paced, interdisciplinary R&D environment.
Preferred (Nice-to-Have) Qualifications
- UAV Licensing: Active FAA Part 107 Remote Pilot License, or willingness/ability to obtain one.
- Specialized Sensing Experience: Experience or academic familiarity with radar remote sensing, cosmic ray neutron sensing, or micro-meteorological instrumentation.
- Software Tools: Familiarity with photogrammetry software (e.g., Pix4D, Agisoft Metashape) and cloud geospatial platforms (e.g., Google Earth Engine).
Are you a good match? Apply today! We seek applicants from all backgrounds to ensure we get the best, most creative talent on our team.
Corteva announced to separate our current advanced seed and genetics business to establish a standalone company, operating as Vylor, Inc. The process of the planned separation is anticipated to be completed the fourth quarter of 2026, subject to legal requirements and board approval. Should you accept this position, it is anticipated that, following conclusion of the separation, you would be an employee of Vylor, Inc. and your employment would be governed by Vylor, Inc. employment processes, programs, policies, and benefit plans. In that case, details of any planned changes would be provided to you by Vylor, Inc. at an appropriate time and subject to any necessary consultation processes.
Vylor is an equal opportunity employer. We are committed to embracing our differences to enrich lives, advance innovation, and boost company performance. Qualified applicants will be considered without regard to race, color, religion, creed, sex, sexual orientation, gender identity, marital status, national origin, age, military or veteran status, pregnancy related conditions (including pregnancy, childbirth, or related medical conditions), disability or any other protected status in accordance with federal, state, or local laws.