Research Intern, Protein Engineer
Our mission is to make biology easier to engineer. Ginkgo is constructing, editing, and redesigning the living world in order to answer the globe’s growing challenges in health, energy, food, materials, and more. Our bioengineers make use of an in-house automated foundry for designing and building new organisms.
The Protein Engineering Team works to address the complex challenges of enzyme discovery, characterization, and engineering. We utilize state-of-the-art approaches to discover novel enzymes and employ a growing suite of computational protein design tools for rationally designing improvements.
As a Research Intern, Protein Engineer, you will help develop an in silico platform for rational protein design and apply interdisciplinary technologies to address the complex challenge of enzyme engineering. You will support Ginkgo’s ultra high-throughput protein engineering pipelines by building software to design and analyze large experimental datasets.
We are looking for someone who is excited about the promise of synthetic biology and the premier role of biomolecular engineering in biology by design. If you sleep not only to maintain healthy levels of protein in the brain, but also dream of dynamical proteins dancing in conformational ensembles, then you are at the right place.
Please note: this role is primarily remote, but the team will offer multiple sponsored trips to travel to the Boston offices if desired. Candidates can share their preference of internship (May 2023 start, 3 month term) or co-op (January or July 2023 start, 6 month term).
The Ginkgo Bioworks Early Talent program is open to students who will return to their degree programs upon completion of their employment at Ginkgo. Candidates must be enrolled in a United States based institution and/or have work authorization in the United States to be eligible to participate.
- Biomolecular modeling: Learn to model protein sequence and structure using software such as Rosetta, Molecular Dynamics simulations, deep learning tools such as AlphaFold 2, and protein statistical and language models to generate hypotheses and predictions about relationships between protein sequence, structure, dynamics, and function
- Biological data processing: Train mathematical models for the analysis of large datasets to critique current hypotheses, spark new ones, and provide actionable information to aid in protein design tasks.
- Protein engineering: Rational design of large libraries for high-throughput experimental characterization such as activity screens, multiplexed mutagenesis assays, and display technologies.
- Streamline workflows: Work in a team to automate routine tasks and develop software to integrate and harmonize large biological datasets from multiple sources for mechanistic interpretation.
- Interdisciplinary research: Flair for collaboration between scientists, who may speak somewhat different scientific languages, but all share a common passion for synthetic biology.
- Currently enrolled in a bachelor’s, master’s, or PhD program in bioengineering, biophysics, biochemistry, structural biology, physics, computer science, computational biology, quantitative biology, or a related field.
- Experience with at least one software programming language (Python is preferred).
- Enthusiasm to learn new techniques and strong curiosity of areas of biology previously unknown to you.
Preferred Capabilities and Experience
- Exposure to at least one type of molecular modeling software such as PyMOL, Rosetta, Schrodinger, Molecular Operating Environment (MOE) a plus.
- Familiarity with developing quantitative models for interpretation of biological data, and applying the learnings to generate hypotheses and testable predictions a plus. Experience with machine learning for data analysis is a plus.
- Experience in visualizing and analyzing protein structures (e.g. PyMol); applying insights, such as biophysical interactions, for generating hypotheses for interpretation of biological data and industrial bioengineering is a plus.
- Exposure to the use of computational tools for the purpose of rational protein engineering, or to understand relationships between sequence, structure, function.
- Wet lab skills (or knowledge of what a wet lab looks like) a plus.
We also feel that it’s important to point out the obvious here – there’s a serious lack of diversity in our industry, and that needs to change. Our goal is to help drive that change. Ginkgo is deeply committed to diversity, equity, and inclusion in all of its practices, especially when it comes to growing our team. Our culture promotes inclusion and embraces how rewarding it is to work with people from all walks of life.
We’re developing a powerful biological engineering platform, so we must remain mindful of the many ways our technology can – and will – impact people around the world. We care about how our platform is used, and having a diverse team to build it gives us the best chance that it’s something we’ll be proud of as it continues to grow. Therefore, it’s critical that we incorporate the diverse voices and visions of all those who play a role in the future of biology.
It is the policy of Ginkgo Bioworks to provide equal employment opportunities to all employees and employment applicants.