Seed Production Research Associate
Pubblicato il 14-10-2026 - Bayer in Olmeneta
At Bayer we’re visionaries, driven to solve the world’s toughest challenges and striving for a world where ,Health for all, Hunger for none’ is no longer a dream, but a real possibility. We’re doing it with energy, curiosity and sheer dedication, always learning from unique perspectives of those around us, expanding our thinking, growing our capabilities and redefining ‘impossible’. There are so many reasons to join us. If you’re hungry to build a varied and meaningful career in a community of brilliant and diverse minds to make a real difference, there’s only one choice.
Seed Production Research Associate (m/f/d)
Bayer Crop Science is a leading agricultural company specializing in innovative crop protection products, seeds, and digital solutions to help farmers sustainably increase productivity.
The Seed Production Research Associate is accountable for planning and executing the Breeding strategies to produce Corn seeds that will feed diverse pipelines across EME aligned with scientists from P Design and P Development.
This position requires a strong knowledge in Corn seed production operations with a strong emphasis on Corn agronomy and for the experimental design of nursery field.
This role involves overseeing the daily operations within the Seed Production workflows, focusing on efficient resource planning, safety protocols, and quality assurance initiatives.
YOUR TASKS AND RESPONSIBILITIES
- Responsible for the experimental design and management of nurseries in the field and for the evaluation of experimental fields
- Oversee farm-related activities such as field preparation, irrigation, planting, harvesting, and maintenance as needed
- Responsible for planting and harvesting Corn experimental fields (inbred production) with a focus on corn agronomy
- Manage data collection equipment and train the team to carry out evaluations
- Responsible for data processing and analysis using company-provided software, generating graphical visualizations to support decision-