Computer Vision and Data Analysis Co-Op

In this role you will analyze and summarize data generated from field trials through digital phenotyping applying modern computer vision and machine learning methods to support decision-making and identify opportunities for system and process improvements in collaboration with Field Testing Data Science and Computer Vision teams.

This position is based on a hybrid work model at the Bayer Crop Science facility in Chesterfield Missouri. Regional travel includes nearby field testing sites in Illinois with potential travel to other Midwest and Midsouth locations.

YOUR TASKS AND RESPONSIBILITIES

The primary responsibilities of this role include:

• Analyze and interpret imagery and metrics generated from field trial data using advanced machine learning and computer vision techniques;
• Collaborate closely with Field Testing and Data Science partners to integrate digital phenotyping insights into data analysis and model development;
• Support experimental design by integrating insights from field assessments (UAV remote sensing and manual methods);
• Contribute to system and workflow improvements by applying creativity and problemsolving to largescale data challenges.

WHO YOU ARE

Bayer seeks an incumbent who possesses the following:

Required Qualifications:

• Active M.S. or Ph.D. candidate in a relevant discipline (data science precision agriculture agricultural engineering plant physiology crop science entomology weed science or pathology);
• Proficiency in Python and experience with deep learning frameworks such as PyTorch TensorFlow or JAX;
• Solid understanding of core machine learning concepts (loss functions regularization optimization methods such as SGD/Adam and learning rate scheduling);
• Familiarity with agricultural research and field trial methodologies;
• Basic knowledge of remote sensing technologies;
• Ability to work collaboratively across areas of expertise.

Preferred Qualifications:

• Handson experience with modern architectures such as ResNet UNet DeepLab YOLO SegFormer SAM and Vision Transformers;
• Experience with creating and managing largescale datasets including the use of tools like Hugging Face Datasets;
• One to two years of UAV imaging experience;
• Strong analytical and problemsolving skills;
• Experience with cloud platforms (AWS GCP or Azure);
• FAA Part 107 license to operate UAVs or ability to obtain before the start date.

Employees can expect to be paid a salary of approximately between $22.75 to $47.75. Additional compensation may include a bonus or commission (if relevant). Additional benefits may include health care vision dental retirement PTO sick leave etc (if relevant). This salary (or salary range) is merely an estimate and may vary based on an applicants location market data/ranges an applicants skills and prior relevant experience certain degrees and certifications and other relevant factors.

This posting will be available for application until at least March 19 2027