Computational Scientist (Mass Spectrometry)

Axiom Bio is building AI systems for drug discovery to predict human toxicity more accurately. The Computational Scientist will develop and scale computational workflows for mass spectrometry data, aiming to enhance the understanding of biochemical states and support toxicity prediction.

Responsibilities:

• Analyze large-scale biological mass spectrometry datasets, primarily LC-MS/MS, across metabolomics, lipidomics, proteomics, and reactive metabolite workflows
• Build, improve, and scale computational pipelines for untargeted LC-MS/MS analysis using tools such as MZmine, OpenMS, MS-DIAL, GNPS, Skyline, or custom internal software
• Develop workflows for peak detection, alignment, normalization, annotation, batch correction, QC, feature filtering, compound identification, and downstream biological interpretation
• Turn raw mass spec data into model-ready representations that can be used by machine learning systems and mechanistic reasoning agents
• Work with biology, chemistry, ML, engineering, and lab teams to design, debug, and improve high-throughput LC-MS/MS assays
• Extract actionable biological insights from mass spec data, including pathway-level changes, metabolic signatures, lipid remodeling, protein abundance changes, and evidence for specific toxicity mechanisms
• Help build datasets that connect chemical structure, dose, exposure, cellular phenotype, biochemical state, and human toxicity outcomes
• Develop quality control systems for high-throughput mass spectrometry datasets, including instrument performance, sample quality, replicate concordance, batch effects, missingness, drift, and annotation confidence
• Collaborate with ML researchers to build models that use mass spec features to improve toxicity prediction
• Investigate where mass spec helps explain model errors, reveals missing biology, or identifies mechanisms not visible from imaging, transcriptomics, or standard biochemical assays
• Design new strategies for expanding Axiom’s mass spec data generation based on model performance, biological coverage, and customer needs
• Help make mass spectrometry data interpretable and useful to drug hunters, toxicologists, and Axiom’s internal AI agents