Computer Vision and Data Analysis Co-Op

In this role, you will analyze and summarise 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.

Responsibilities

• 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 problem-solving to large-scale data challenges.

Requirements

• 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

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

Compensation

• Salary of approximately between $22.75 to $47.75.
• Additional compensation may include a bonus or commission.
• Additional benefits may include health care, vision, dental, retirement, PTO, sick leave, etc.