Senior Scientist, Therapeutic Discovery

Flagship Pioneering, Inc.•Cambridge, MA

17h•$126,000 - $181,500

About The Position

FL121 is a privately held biotechnology company engineering nature to build next generation peptide therapeutics. By harnessing naturally occurring chemistry and pairing it with sophisticated high-throughput screening technology, we will unlock the future of de novo drug design via curated data creation and model training. We are building a therapeutic discovery platform that integrates AI/ML, biosynthetic enzyme discovery, advanced analytical readouts (with a strong emphasis on LC‑MS), and innovative screening technologies. This role will own hybrid Design–Build–Test–Learn cycles—spanning computational prioritization, hands-on experimental execution, and multimodal data integration—to drive rapid, data-grounded decisions.

Requirements

PhD in a relevant field; strong record of independent technical ownership, with 5+ years of experience
True hybrid skillset: Python/R (stats, reproducibility, version control) + strong bench execution (molecular biology/expression, enzyme assays, library-oriented experimentation).
Demonstrated expertise in enzyme discovery and characterization; ML/representation or structure-informed approaches a plus.
Working knowledge of LC‑MS(/MS) in molecular discovery and proficiency with sequencing-enabled measurements (e.g., NGS-based readouts).
Experience designing/running screening or selection workflows and translating outcomes into follow-on experimental plans; strong cross-audience communication.

Nice To Haves

Comfort in ambiguity; can move between strategy and execution.
Creative and rigorous in experimental design, documentation, and data interpretation.
Collaborative communicator; gives/receives feedback effectively.
Grit and agility in fast-moving environments.

Responsibilities

Prioritize biosynthetic pathways computationally; translate into build hypotheses.
Execute wet-lab workflows to build and interrogate genetic designs and run screening/selection assays tied to therapeutic-relevant readouts.
Build reproducible pipelines to integrate with multi-modal data structures that drive therapeutic candidate prioritization strategies.
Partner cross-functionally with analytical chemistry and AI-enabled discovery workflows to deliver platform proof of concept data.