Plant Health Digital Phenomics Intern

In this 3month internship you will contribute to the success of the Breeding Plant Health team by building and validating controlledenvironment digital phenomics solutions. You will bridge plant pathology with digital innovation applying image analysis artificial intelligence and datadriven approaches to transform disease phenotyping from manual visual scoring into highthroughput automated quantitative trait extraction that directly informs Bayers breeding advancement decisions in row crops. This role is ideal for a technologysavvy plant scientist passionate about combining plant health agronomy and quantitative data analysis to solve realworld biological challenges.

The internship is located in Chesterfield MO and is 100% inperson. The intern will have the opportunity to increase business acumen and professional development through inperson and virtual networking opportunities throughout the term.

YOUR TASKS AND RESPONSIBILITIES

The primary responsibilities of this role include:

• Work alongside scientists in controlledenvironment phenotyping and digital image/data analysis to support the Breeding Plant Health team across key pathosystems;
• Develop and validate automated image analysis pipelines (AI/ML) to extract disease and phenotypic traits from imagery benchmarking results against manual scores and genomic prediction indices;
• Solve technical and operational challenges independently drawing on prior experience and consultation with team members to complete experiments on time;
• Achieve commitment to safety and compliance adhering to safety protocols and best practices in greenhouse growth chamber and lab environments.

WHO YOU ARE

Bayer seeks an incumbent who possesses the following:

Required Qualifications:

• Currently pursuing a graduate degree (M.S. or Ph.D.) in a plant science discipline or a computational discipline (Computer Science Computer Vision Data Science or Biosystems/Agricultural Engineering) with demonstrated interest at the intersection of crop health and digital/AIdriven analysis;
• Experience in controlledenvironment research and plant disease digital phenotyping with interest in applying AI/ML tools to crop health and breeding challenges;
• Experience with data analysis statistical methods and programming (Python R or similar) for processing and interpreting plant disease phenotyping datasets;
• Familiarity with computer vision image analysis or machine learning concepts including image annotation object detection segmentation or predictive modeling;
• Selfmotivated and takes initiative to meet goals with minimal supervision; proven problemsolver;
• Willingness and ability to relocate for the 3month internship to Chesterfield MO.

Preferred Qualifications:

• Experience developing image segmentation object detection or classification pipelines using tools such as OpenCV Segment Anything Model (SAM/SAM2) YOLO or similar frameworks;
• Handson experience with image processing computer vision or related AI/ML workflows for plant disease or agronomic trait analysis (as specified in the full job description).

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