ML Researcher
Monarch· R&D
Emeryville, CaliforniaFull-timePosted 1mo ago
About the role
Develop learning methods to turn repeated assays into better scientific decisions by leveraging molecular information, formulation and dose, assay metadata, video-derived behavior, and laboratory context to inform more informative experiments.
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
Qualifications
- Ph.D. or equivalent research record in machine learning, statistics, computational science, or a closely related field
- Demonstrated ability to formulate open-ended research questions, build strong baselines, and design evaluations that survive distribution shift
- Strong software skills in Python and a modern machine-learning framework
- Experience working with noisy, limited, multimodal, or experimentally generated datasets
- Ability to move between theory, implementation, and scientific interpretation
Skills
Required:Open-ended research question framingBaseline and evaluation designPython
Benefits
- Equity compensation
Last updated Oct 7, 2026. Interested? Apply on the company site.
About Monarch
Monarch is developing a scalable, precision-based approach to protect crops from insects.
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