Computer Vision and Data Analysis Co-Op

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 RESPONSIBILITIESThe 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 problem‑solving to large‑scale data challenges.WHO YOU AREBayer 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: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.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 applicant’s location, market data/ranges, an applicant’s 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, 2027YOUR APPLICATIONBayer offers a wide variety of competitive compensation and benefits programs. If you meet the requirements of this unique opportunity, and want to impact our mission Health for all, Hunger for none, we encourage you to apply now. Be part of something bigger. Be you. Be Bayer. To all recruitment agencies: Bayer does not accept unsolicited third party resumes. Bayer is an Equal Opportunity Employer/Disabled/Veterans Bayer is committed to providing access and reasonable accommodations in its application process for individuals with disabilities and encourages applicants with disabilities to request any needed accommodation(s) using the contact information below. Equal Opportunity Employer Statement: Notice for U.S. Visitors: All information on this site is subject to compliance with local rule and regulations as they may vary from time to time and across different geographies, including, without limitation, U.S. Executive Orders.Bayer is an E-Verify Employer.Location:United States : Missouri : Chesterfield Division:Crop Science Reference Code:883370 Contact UsEmail:View email address on click.appcast.io