Computational Scientist, Toxicity Modeling & Drug Safety

Axiom Bio; San Francisco (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

Axiom Bio is building a high-throughput liver safety platform that blends biology and AI to predict drug toxicity. You will analyze multimodal datasets, identify mechanisms of injury, and drive reproducible workflows across imaging, transcriptomics, and mass spectrometry.

You will partner with ML scientists to refine models, interpret signals, and propose additional measurements to close gaps. Join a mission to make medicines safer through data-driven insights.

Qualifications

• Strong background in integrating biology with ML and data analysis.
• Ability to work with large, multimodal datasets and extract robust features.
• Experience in QC, reproducibility, and experimental variability assessment.
• Comfort interpreting model predictions with mechanistic biology context.

Responsibilities

• Lead the analysis of multimodal toxicity datasets to derive biological insights.
• Characterize drug responses in primary human cells and multicellular systems.
• Develop QC methods for batch effects and assay performance.
• Collaborate with ML scientists to improve predictive models.
• Investigate model behavior and identify failure modes.
• Design protocols and assays to capture relevant biology.
• Interpret compound toxicity and inform drug development decisions.
• Help build AI systems that explain mechanisms and weigh evidence.

Skills

Python + scientific stack

High-content imaging

Statistical modeling

Image analysis tools

Tools

CellProfiler

Cellpose

napari

OpenCV

scikit-image

Pandas

NumPy

SciPy

Job description

Axiom Bio is building a high-throughput liver safety platform that blends biology and AI to predict drug toxicity. You will analyze multimodal datasets, identify mechanisms of injury, and drive reproducible workflows across imaging, transcriptomics, and mass spectrometry.

You will partner with ML scientists to refine models, interpret signals, and propose additional measurements to close gaps. Join a mission to make medicines safer through data-driven insights.