Job Description

Machine Learning Computational Biologist

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** Machine Learning Computational Biologist **

I am working with a well-funded, AI-driven biotech who are building something really exciting at the intersection of machine learning, high-content imaging, and experimental biology, and they’re looking for a Computational Biologist to join the team.

In this role, you’d be working on some of the largest and most complex toxicity datasets in the world. The focus is on figuring out what biology is actually driving the signal, and where models go wrong. You'll be working side-by-side with ML researchers, assay developers, and drug discovery scientists to connect the dots between chemical structure, imaging readouts, and biological response.

What you'll be doing :

• Digging into large, noisy biological datasets to find clear, actionable insights
• Running deep-dive analyses on ML models to understand what they've actually learned
• Helping design new imaging assays that generate data useful for prediction
• Building pipelines to clean, QC, and analyze high-content imaging data
• Investigating toxicity across systems like liver, heart, kidney, and immune tissue
• Working closely with drug discovery teams to help interpret compound toxicity

Tech & tools that would help:

• Experience with imaging tools like CellProfiler, Cellpose, or similar
• Solid grasp of stats, dimensionality reduction, curve fitting, and ML basics
• Background in high-throughput screening, cell painting, or assay automation is a plus

What they’re looking for:

• Someone who’s fluent in both biology and code, or a strong biologist who’s picked up coding to go deeper in their work
• A sharp eye for signal vs noise in messy biological data
• A genuine curiosity about how biology works, how software models interpret it, and how to bridge the two
• Someone who cares about data quality, clear thinking, and asking the right scientific questions
• Bonus if you’ve published in this space or contributed new computational methods

If you're excited by the idea of building tools and methods that can actually help de-risk drug development this could be a great fit.

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Full-time

Job function

• Job function

  Research, Engineering, and Science

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