Scientist I, Synthetic Biology

Generate Biomedicines•Somerville, MA

8d•$102,000 - $130,000

About The Position

Generate Biomedicines’ Prototyping Lab builds experimental systems to measure protein function at scale, combining synthetic biology, large DNA libraries, high-throughput assays, and machine learning. The team is hiring two Scientists to develop pooled screens that test hundreds of thousands of protein variants in parallel to identify protein binders and modulators. The work involves DNA library design, pooled in vitro protein display, and NGS-based enrichment analysis. One of the two roles additionally calls for experience in mammalian cell engineering and membrane protein studies. Computational modeling or statistical analysis experience can help connect experimental design to the quality and usefulness of the resulting data. The Scientist will collaborate closely with Protein Sciences and Machine Learning teams to build screening approaches that provide clear, quantitative insight into protein function. The role offers scope to originate and advance technologies in collaboration with a well-resourced biotech team. Generate Biomedicines is a clinical-stage generative biology company that integrates machine learning with large-scale experimentation to design proteins with defined biological intent and develop protein-based medicines. Founded in 2018, the company has clinical and preclinical programs across multiple disease areas and protein modalities.

Requirements

PhD in synthetic biology, systems biology, bioengineering, or a related field, with 0–1 year of experience; alternatively, a bachelor’s or master’s degree with at least 6 years of highly relevant experience.
Hands-on experience designing and running pooled binding screens, ideally using both purified proteins and cell-based assays.
Experience designing and building pooled DNA libraries and using next-generation sequencing to track enrichment in selection campaigns.
Ability to interpret complex screening data and write scripts in Python or a similar language.
Quantitative reasoning and sound experimental judgment to assess data quality, troubleshoot assays, and guide next steps.
Ownership of applied biology projects from initial concept through execution, analysis, and delivery.
Intellectual curiosity, willingness to share expertise, and collaborative approach to helping colleagues grow.
High level of cross-functional autonomy and self-motivation.

Nice To Haves

For one of the two roles, strong cell-culture skills and experience engineering cell lines for screening using methods such as CRISPR, lentiviral transduction, or transposon-based integration.
For one of the two roles, experience working with membrane proteins is highly preferred.
Experience in computational modeling or statistical analysis.
Familiarity with recombinant protein production, purification, and/or binding assays.
Familiarity with AI-assisted coding tools such as Cursor or other LLM-based platforms.

Responsibilities

Build pooled screening workflows for scalable protein-binding and functional readouts, from assay setup through data interpretation.
Collaboratively establish reliable assay conditions, quantitative measures, and handoff plans that enable project teams to maximize platform utility.
Identify opportunities to test unconventional hypotheses, applying strong concepts to accelerate drug programs and support IP filings.
Synthesize findings into clear recommendations and present them in writing and presentations to colleagues across disciplines.
Use quantitative reasoning, modeling, and critical literature review to inform experimental choices.
Take ownership of applied biology projects from initial concept through execution, analysis, and delivery.
Troubleshoot assays, assess data quality, and guide next steps using quantitative reasoning and experimental judgment.
Collaborate across disciplines and share expertise to help colleagues grow through mentorship.