# Computer Vision and Data Analysis Co-Op

**Company**: Bayer Crop Science
**Location**: Chesterfield, Missouri
**Work arrangement**: hybrid
**Job type**: internship
**Salary**: $22.75 to $47.75
**Category**: IT
**Industry**: Agriculture

**Apply**: https://talent.bayer.com/careers/job/562949978464391?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_493baf45-c17

## Description

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.

## Skills

### Required
- Python
- deep learning frameworks
- machine learning
- agricultural research
- remote sensing technologies

### Nice to have
- ResNet
- UNet
- DeepLab
- YOLO
- SegFormer
- SAM
- Vision Transformers
- Hugging Face Datasets
- UAV imaging
- cloud platforms
- FAA Part 107 license

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Source: [Apply at talent.bayer.com](https://talent.bayer.com/careers/job/562949978464391?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)