Digital Plant Phenotyping & Machine Learning Co-Op

In this role you will implement and optimize advanced deep learning and machine learning approaches to generate actionable insights from imaging and sensor data supporting data-driven decision making in plant phenotyping and agricultural research.

YOUR TASKS AND RESPONSIBILITIES

The primary responsibilities of this role are to:

• Implement and optimize deep learning and machine learning algorithms leveraging generative models for actionable insights and solutions;
• Evaluate needs recommend experiments and projects advocate for novel algorithmic pursuits and inform strategic decisions;
• Utilize imaging and sensor technologies to collect and analyze phenotypic data such as plant growth plant development and biotic and abiotic responses;
• Communicate results in a timely and organized fashion to project teams and key stakeholders through scientific reports and presentations;
• Solve complex problems autonomously requiring original thinking creativity and deductive reasoning and apply scientific principles to the design and interpretation of scientific experiments;
• Perform multiple experimental protocols under supervision as needed;
• Prioritize and coordinate work within a matrixed testing environment while maintaining detailed record keeping and required documentation;
• Demonstrate strong commitment to safety and compliance by adhering to safety protocols and best practices.

WHO YOU ARE

Bayer seeks an incumbent who possesses the following:

Required Qualifications:

• Enrollment in a masters or Ph.D. program in Computer Science Electrical Engineering or an agricultural science program with a focus on computer vision or machine learning;
• Solid foundation in Python programming and familiarity with deep learning frameworks such as TensorFlow or PyTorch;
• Experience with model architectures and tools including ResNet YOLO R-CNN DeepLab GANs VAEs and Transformers;
• Experience with hardware and sensing platforms such as RGB-D cameras LiDAR sensors robotics and other imaging or phenotyping systems.

Preferred Qualifications:

• Previous experience with cloud platforms for model deployment including AWS Google Cloud or Azure;
• Experience using computer modeling techniques for plant development and image-based plant phenotyping;
• Experience implementing machine learning and statistical models to identify or evaluate biotic and/or abiotic stresses in plants.

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