Nature has evolved billions of useful molecular nanotechnology devices in the form of genes, across the tree of life. We catalog, refine, and remix these genetic components to engineer new biological systems.
Biology is complex, and genetic engineering unlocks an unbounded design space. Computational tools are critical to design and model complex biophysical systems and move synthetic biology beyond traditional brute force screening.
Genome-scale, multi-omics measurement technologies provide deep views into the cell. These techniques permit pathway analysis at the scale of a whole cell, and inspection down at single-nucleotide resolution.
We are developing machine learning algorithms that bridge large-scale datasets with mechanistic models of biology. Artificial intelligence can augment human capabilities to design and understand biological complexity.
We endeavor to build the genetic programs powering the world's most impactful biotechnologies. Our ambitious long-term goal is to enable design of entire genomes from the ground up. Come help us build this future.
Synthetic biology has ushered in an era where medicines can be iteratively engineered rather than discovered. We focus on advancing the design and manufacture of genetically engineered therapeutics.
Ours is a culture of recombination, where diverse expertise and experiences intermix. Our team spans synthetic biology, machine learning, computational biology, and automation.
Research Associate II
VP Software Engineering
Intern, Synthetic Biology
Co-Founder & CEO
Head of Scientific Operations
Biological Data Scientist
Machine Learning Engineer
If you share our drive to design living systems, we’re interested in hearing from you.
700 Main St.
Cambridge, MA 02139