Sr. Machine Learning Researcher

This role involves developing next-generation domain-aware machine learning models for agriculture by integrating scientific knowledge from genetics, crop physiology, and environmental dynamics into data-driven frameworks. The position requires designing interpretable AI architectures and implementing rigorous uncertainty quantification to support genomic selection and genome editing target identification. Collaboration with interdisciplinary teams is essential to translate domain expertise into model architecture decisions and validate outputs against biological ground truth.