ML Researcher

Monarch Crops is seeking an ML Researcher to develop learning methods that improve scientific decision-making from repeated assays. The role focuses on multimodal research models, active learning, sequential experiment selection, rigorous evaluation under distribution shift, and translating model findings into improved experiments and scientific understanding.

Responsibilities:

• Research models that combine molecular information, formulation and dose, assay metadata, video-derived behavior, and laboratory context
• Develop active-learning and sequential experiment-selection methods that balance predicted efficacy, uncertainty, novelty, and information value
• Define retrospective and prospective evaluations, including holdouts by chemical scaffold, laboratory, colony, and time
• Investigate which behavioral signals generalize across experiments and which reflect confounding, measurement noise, or laboratory-specific effects
• Translate model failures into new labels, assay variants, controls, or experiments that improve the next training cycle
• Communicate results with enough precision that experimental scientists can understand why a recommendation should or should not be trusted