Digital Plant Phenotyping & Machine Learning Intern

Your Tasks And Responsibilities

• 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

Required Qualifications

• Enrollment in a master's 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