In Bayer’s Crop Science division, we shape agriculture through breakthrough innovation that helps to nourish our growing world, preserve natural resources and deliver better solutions for all farmers. Using the creative spark that comes from human ingenuity, we seek to deliver world-class innovation, set new standards in sustainability, and drive our digital transformation. Our products include high-performance seeds & traits, crop protection solutions, and digital farming tools.

YOUR TASKS AND RESPONSIBILITIES

The primary responsibilities of this role, Phenomic-Assisted Breeding Intern, are to: 

• Coordinate with field testing team to develop data collection strategy;
• Work with a cross-disciplinary team to develop and deploy proximal sensors and remote sensing technologies for field-based phenotyping efforts;
• Process and analyze high-dimensional phenomic data to enable the development of predictive modeling;
• Leverage phenomic information to develop phenomic-assisted breeding strategies to reduce logistical requirements associated with current testing strategy and improve selection accuracy;
• Assist in the development of down-stream image processing, model development, and validation of model outputs;
• Be able to effectively communicate results and outcomes at meetings and internal conferences;
• Ensure completion of Phase 1 phenomic-assisted breeding initiative.

WHO YOU ARE

Your success will be driven by your demonstration of our LIFE values.  More specifically related to this position, Bayer seeks an incumbent who possesses the following:

Required Qualifications:

• Currently enrolled in a Master’s degree, or Ph.D. in the following fields of study: plant breeding, agronomy, phenomics, computer science or other fields of study involved in deploying sensor in biological systems for development of predictive models;
• Familiarity with the following; plant breeding methodologies, high-throughput phenotyping, predictive model development, and computer vision workflow;
• Experience working with ‘omics data and development of data processing pipelines for ingestion into predictive models;
• Experience with R, Python, Excel, and other data manipulation and visualization tools;
• Communication skills to transcend knowledge gaps between scientific domains;
• Willingness to work outside to develop novel phenotyping systems and to collect phenotypic data;
• Valid driver’s license to travel to and from fields.