Axiom Bio · 3 weeks ago
Computational Scientist (Biology)
San Francisco Bay Area
Full-time
Onsite
Mid, Senior LevelAxiom Bio is focused on building the future of preclinical safety using AI models to predict human toxicity. The role of Computational Scientist involves analyzing large biological datasets, developing predictive models, and collaborating with leading drug discovery teams to enhance the understanding of molecule toxicity.
Artificial Intelligence (AI)Biotechnology
Responsibilities
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
Qualification
Required
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
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
Preferred
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
Company
Axiom Bio
Axiom Bio helps scientists eliminate molecular toxicity by offering the most accurate and affordable predictive models.
Founded in 2024
11-50 employees
Funding
Current Stage
Early StageTotal Funding
unknown2025-07-01Seed
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