Founding Computational Biologist - Metabolomics

We are building computational systems to discover and develop small molecule medicines from fungi. Nearly half of all oral medicines originate from natural molecules, yet systematic discovery from nature has historically been slow. Advances in mass spectrometry and computation now make it possible to systematically explore nature’s chemical diversity at scale.

We are looking for a founding computational biologist to architect and scale the metabolomics workflows that power our discovery efforts.

You will own the systems that transform raw LC-MS/MS data from fungal strains into structured, reproducible outputs used for screening, prioritization, and downstream modeling. This role sits at the interface of metabolomics, biology, and machine learning, and involves close collaboration with experimental and ML teams.

This is a hands-on role in an early-stage company with significant autonomy and technical responsibility.

What you’ll own:

• End-to-end untargeted LC-MS/MS analysis workflows (such as MZMine, OpenMS, SIRIUS, GNPS)
• Designing data infrastructure that scales to large strain libraries and high-volume metabolomic datasets
• Internal knowledge graphs / ontologies linking spectra, structural hypotheses, and biological outcomes
• Building feedback loops between experimental and computational work

Core experience

• Experience building custom computational pipelines in Python for large biological or chemical datasets
• Experience developing and scaling untargeted metabolomics workflows for LC-MS/MS data
• Ability to apply computational analysis to answer concrete biological questions

Nice-to-haves

• Familiarity with tools such as MZMine, SIRIUS, CANOPUS, GNPS, MS2
  
  Prop, ICEBERG, or related platforms
• Experience integrating metabolomics with bioactivity or phenotypic screening data
• Exposure to cloud or HPC environments
• Experience with machine learning methods applied to molecular data

We value agency, technical depth, and learning velocity more than years of experience.

If you find this exciting and think you'd be a great fit, we’d love to hear from you. We can go from first conversation to offer decision in days.