ML Research Scientist: Active-Learning for Experimental Design

mZero; Emeryville (CA); On-site; USD 160,000 - 260,000; Full time

Benefits offered by this job

Equity

Job summary

mZero in Emeryville, CA is seeking a researcher to advance learning methods that use prior compound, assay, and behavior data to recommend informative experiments.

The role combines theory, implementation, and scientific interpretation, requiring a PhD and strong Python skills, and offers full-time in-office work with equity. You will collaborate with experimental scientists to translate insights into actionable experiments.

Qualifications

• PhD or equivalent in ML, statistics, computational science, or related field.
• Ability to formulate open-ended research questions and design robust baselines.
• Strong Python skills and a modern ML framework.
• Experience with noisy, multimodal, or experimentally generated data.
• Ability to move between theory, implementation, and scientific interpretation.

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

Skills

Python

Machine learning

Multimodal data

Open-ended research

Evaluation design

Scientific communication

Education

Ph.D. or equivalent in ML/Statistics/Computational Science

Job description

mZero in Emeryville, CA is seeking a researcher to advance learning methods that use prior compound, assay, and behavior data to recommend informative experiments.

The role combines theory, implementation, and scientific interpretation, requiring a PhD and strong Python skills, and offers full-time in-office work with equity. You will collaborate with experimental scientists to translate insights into actionable experiments.