Digital Plant Phenotyping & Machine Learning Co-Op

Role: Implement and optimize deep learning and machine learning models for plant phenotyping, leveraging imaging and sensor data to generate actionable insights. Responsibilities: develop algorithms, evaluate project needs, recommend experiments, analyze phenotypic traits such as growth and stress responses, communicate findings to stakeholders, and ensure safety compliance. Qualifications: enrolled in a master's or Ph.D. program in Computer Science, Electrical Engineering, or agricultural science focused on machine learning or computer vision; proficient in Python and familiar with frameworks like TensorFlow or PyTorch; experienced with models such as ResNet, YOLO, GANs, and hardware platforms like RGB-D cameras and LiDAR. Preferred: experience with cloud deployment (AWS, GCP, Azure), plant modeling, and stress evaluation. HighValue: plant phenotyping, deep learning/model development, sensor data analysis, biological stress assessment. WorkSetup: based in Missouri, USA; specifics on travel are not provided.