Computational Scientist (Biology)

Axiom Bio; San Francisco (CA); On-site; USD 69,000 - 78,000; Full time

Job summary

Axiom Bio is looking for a Computational Scientist dedicated to building innovative AI solutions for preclinical safety. This role involves analyzing complex biological data and collaborating with top professionals to improve drug discovery processes. Candidates must possess strong programming skills and a deep understanding of biology to make impactful contributions.

Qualifications

• Solid mathematical and statistical background.
• Experience analyzing multimodal toxicity datasets.
• Exceptional ability to bridge wet lab protocols and machine learning algorithms.

Responsibilities

• Drive the exploration and analysis of multimodal toxicity datasets.
• Transform biological data into actionable insights.
• Collaborate with teams to enhance model accuracy.

Skills

Python

Pandas

Numpy

Jupyter Notebook

Imaging data analysis

Quality control

Job description

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Charter:

Be a founding member of a team setting out to build the first accurate AI systems for replacing lab and animal toxicity experiments with AI models.

Charter:

Be a founding member of a team setting out to build the first accurate AI systems for replacing lab and animal toxicity experiments with AI models.

About Axiom:

At Axiom, we’re building the future of preclinical safety with AI models that predict human toxicity better than animal tests and legacy in vitro assays. We're looking for a computational biologist who thrives at the intersection of high-dimensional data, cell biology, and machine learning. You’ll work alongside a world-class team of scientists and engineers to develop predictive models from imaging and functional biochemical readouts—and use them to guide decisions in real-world drug development. This role is perfect for someone who’s excited to translate biological signal into actionable insights, shape the design of novel assays, and collaborate directly with leading pharma companies to make drug discovery faster, safer, and more human-relevant.

What are we looking for:

At the highest level, we only want to hire people who deeply inspire us and relentlessly push us to be better. They must level up the entire team, bringing significant energy and a sense of awe. High agency is critical: they see what’s important and they do it. Doing is the key but it should be guided by great taste for what truly matters. We’re looking for folks doing those niche hobbies and activities, the ones that might not make sense at first glance, but eventually reveal profound depth and passion when you dive in with them. These individuals act with intentionality or whimsical naivety like an immigrant in a new country, a performer trying to break out, or someone teaching themselves to code or garden. There must be a deep curiosity for all facets of Axiom, an ambition fueling their exploration of what we do. They want to do something here, to dive in headfirst, but they know they need to learn more, so they search with an insatiable hunger. They need to be cracked, technically excellent, obsessive masters of their craft. They're irrational; they could work in big tech, but they know it will not satisfy them. They want the pain of doing something brutally hard along with the riches and glory when it finally works.

What you will do:

• Drive the exploration and analysis of the world's largest multimodal toxicity datasets.
• Transform noisy, high-dimensional biological data into clear, actionable insights by identifying critical signals.
• Uncover novel biological signals that differentiate safe and toxic drugs.
• Conduct detailed error analyses on machine learning models to elucidate the biology captured by algorithms.
• Invent cutting-edge algorithms at the intersection of computation and biology to model unexplored biological mechanisms.
• Investigate a diverse range of biological systems—including liver, heart, kidney, and immune tissues—to model the relationship between chemical structures and biological responses.
• Collaborate with ML researchers to enhance model accuracy by integrating newly discovered biological insights and data modalities.
• Develop innovative high content imaging assays capable of generating unprecedented datasets for predictive modeling of human tissue toxicity.
• Create quality control processes for massive high content imaging datasets.
• Partner closely with leading drug discovery teams globally, empowering them with deep biological understanding of molecule toxicity profiles.
  
  

We’re especially interested in:

• Python, Pandas, Numpy, Jupyter Notebook
• Solid mathematical and statistical background (curve fitting, dimensionality reduction, stats tests, modeling, traditional imaging algorithms)
• Cellprofiler, Cellpose, imaging data analysis, quality control
• High content imaging, cell painting, assay development
• High throughput screening, automation
  
  

What we look for:

• Biologist who taught themselves to code to do their own analysis.
• You consistently impress fellow biologists with your coding abilities, setting a high standard that others aspire to match and/or envy.
• Possess a unique talent for identifying intricate and subtle biological signals in imaging data, enhancing the accuracy and effectiveness of machine learning models to model the discovered signals.
• Desire to continuously push beyond traditional methodologies to develop novel computational algorithms and approaches for biology.
• Passionate about high-content imaging with a clear ambition to build the world’s largest and most comprehensive datasets.
• Driven by a relentless pursuit of scientific excellence—dedicated to ensuring impeccable data quality, meticulous analyses, and only sharing data of the highest standards.
• Exceptional ability to bridge the gap between wet lab protocols and machine learning algorithms, seamlessly integrating both fields to drive groundbreaking discoveries.
• Obsessive technical curiosity for all things in the wetlab, drylab, and drug discovery.
• Experience publishing and telling great scientific stories in a creditable + inspiring manner.

Seniority level

• Seniority level

  Entry level

Employment type

• Employment type

  Full-time

Job function

• Job function

  Research, Analyst, and Information Technology

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