Computational Biologist (AI/ML Genomics)

TL;DR

Computational Biologist (AI/ML Genomics): Building AI-powered applications that turn biological data into structured predictions for drug discovery in gynecological cancer with an accent on genomics analysis, LLM integration, and reproducible pipelines. Focus on designing prompt architectures, differential expression analysis, pattern recognition in cancer data, and deploying functional software for non-technical users.

Location: Onsite in Cambridge/Boston, MA, USA

Company

Early-stage biotech at the intersection of AI and drug discovery for therapies targeting relapsed gynecological cancers.

What you will do

• Analyze large-scale biological datasets from public sources, including cancer cell lines and patient tumors.
• Perform differential expression analysis, pattern recognition, and biological interpretation of genomics data.
• Build AI-powered applications with LLM API integration for scientifically grounded predictions.
• Develop Python pipelines for reliable processing, analysis, and output of biological data.
• Deploy functional applications usable by non-technical collaborators.
• Contribute to technical direction with potential pathway to co-founder or CTO.

Requirements

• Must work onsite in Cambridge/Boston, MA
• Experience with large-scale biological datasets, gene expression data structure, normalization, and interpretation.
• Proficiency in Python for building data processing pipelines.
• Background in computational biology, bioinformatics, systems biology, or biomedical engineering.
• Understanding of AI value vs. statistical approaches; experience building and deploying applications.
• Comfort with ambiguity and building from scratch in early-stage environment.

Nice to have

• scRNA-seq analysis experience.
• Prior experience at early-stage biotech, research startup, or translational lab.
• Genuine curiosity and builder instinct.

Culture & Benefits

• Equity-based compensation with vesting and cliff, negotiated on commitment.
• Access to LabCentral lab space, genomics infrastructure (10X Chromium X, NextSeq 2000, spectral flow cytometry).
• C10 Labs AI Biohub program with mentorship and Boston biotech ecosystem.
• Genuine thought partnership shaping technical and company direction.