Zymergen, Inc

Founded in 2013, Zymergen marries the latest innovations in data science, automation, and molecular biology to both discover and engineer new molecular products and to improve existing ones. Zymergen uses hypothesis testing based on our deep and broad knowledge, coupled with an atheoretic and automated approach in order to navigate the genomic search space for our customers. This methodology is designed to make discoveries beyond the bounds of human intuition by collecting and analyzing promising data we otherwise might never encounter.

To do this innovative and interdisciplinary research, Zymergen works equally as a software company and a biology company. On the software front, our proprietary infrastructure helps us simultaneously design thousands of “test everything” experiments targeting both on- and off-pathway genes, while allowing us to include other experiments based on rational hypotheses. Our software and IT infrastructure are layered on top of our innovative factory, an automated, modular, full-production facility. This factory is designed so scientists can safely and accurately conduct experiments using automated equipment and workflows. We also combine our platform and data infrastructure with a “host agnostic” approach: Zymergen has proven capabilities to work with the full range of microbes currently used for industrial production, as well as unconventional microbial species. Alongside canonical hosts such as S. cerevisiae and E. coli, we work with a range of other yeasts and other Gram-negative bacteria, as well as filamentous fungi and Gram-positive bacteria.

Our company ultimately sits at the intersection of molecular biology, industrial chemistry, machine learning, data science, and automation systems design. This enables Zymergen to deliver material diversity and performance capabilities not previously possible, with applications across industries -- from agriculture, to industrial chemicals, to pharmaceuticals and more.

Projects for interns will likely fall within the following areas:

• Data science and modeling techniques
• Bioinformatics
• Engineering filamentous fungi

Potential project descriptions can be found in the attachments below. Please note: project descriptions are subject to change. Not all projects may be available at time of internship.

Anticipated number of internship positions: 5