Senior Scientist, Cell Biology

Axiom Bio
South San Francisco, CA
Category Research
Job Description
Role Overview

As a Senior Scientist, Cell Biology at Axiom, you will build human cell models and multiplexed high-content assays to predict drug-induced toxicity and guide drug development. You will partner with robotics engineers, computational scientists, and ML researchers to generate large-scale biological datasets that power frontier AI agents for translational drug discovery.

What You Will Do

You will build human cell models that accurately predict drug-induced toxicity, design and optimize physiologically relevant systems, develop high-content assays, and combine live-cell imaging and other methods to connect changes in cell behavior with underlying molecular mechanisms.

Why It Might Be a Fit

You will be an exceptional experimental scientist with a deep understanding of cell biology and human physiology, inventing and refining biological models and assays to answer questions that established protocols cannot. You will hold your work to extremely rigorous scientific standards and communicate complex science clearly.

Requirements

  • Experience with primary human cell culture, iPSC culture and differentiation, and cell engineering
  • Experience developing physiologically relevant models, including co-cultures, organoids, spheroids, and engineered tissues
  • A strong foundation in cell biology, molecular biology, physiology, and pharmacology
  • Expertise in high-content imaging, Cell Painting, fluorescence microscopy, live-cell imaging, and image-based phenotypic screening
  • Experience developing, miniaturizing, and automating assays for high-throughput screening
  • Experience measuring cell viability, mitochondrial function, oxidative stress, ER stress, apoptosis, inflammation, and other functional responses
  • Familiarity with RNA sequencing, proteomics, metabolomics, and methods that combine multiple biological measurements
  • Strong experimental design and quantitative analysis skills, including dose-response analysis, statistical methods, assay validation, and quality control
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