Computational Protein Engineer

(Full Time) Computational Protein Engineer at Ginkgo Bioworks (United States)

Computational Protein Engineer

Ginkgo Bioworks United States

Date Posted: 08 Jun, 2023

Work Location: Boston, United States

Salary Offered: Not Specified

Job Type: Full Time

Experience Required: No experience required

Remote Work: No

Stock Options: No

Vacancies: 1 available

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 bioinformatics to discover novel enzymes and employ a growing suite of computational protein design tools for rationally designing improvements.

As a Computational Protein Engineer, you will help develop an in silico platform for rational design and apply state-of-the-art computational 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.

Responsibilities

• Protein engineering: Rational design of large libraries for high-throughput experimental characterization such as activity screens, multiplexed mutagenesis assays, and display technologies.
• Biomolecular modeling: Perform structure and sequence modeling of proteins using software such as Rosetta, molecular dynamics simulations, deep learning, 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.
• Model interpretation and application: Understand and predict the effects of sequence variation on protein function and biophysical parameters that are relevant for enzyme and protein engineering and improvement.
• Streamline workflows: Build computational pipelines to automate routine tasks and develop software to integrate and harmonize large biological datasets from multiple sources for mechanistic interpretation.
• Other protein design expertise: We are interested in learning from you! A short, ridiculously non-exhaustive list includes predicting and engineering protein-protein interactions, statistical and deep learning models for protein engineering, antibody engineering, biosensor engineering, de novo protein design, enzymology.
• Interdisciplinary research: Flair for collaboration between scientists, who may speak somewhat different scientific languages, but all share a common passion for synthetic biology.

Desired Experience and Capabilities

• PhD in bioengineering, biophysics, biochemistry, physics, computer science, computational biology, quantitative biology, or related field.
• Significant hands-on technical experience with at least one type of molecular modeling software such as Rosetta, Schrodinger, or Molecular Operating Environment (MOE). Expertise in the computational modeling of biomacromolecules especially for the purposes of rational protein engineering.
• Proficiency with at least one software programming language – Python strongly preferred. Familiarity with best practices for collaborative software development.
• Experience parsing large datasets and applying machine learning to develop data-driven predictive models for interpretation of biological data and industrial bioengineering is a plus.
• Experience applying deep learning to protein engineering tasks is a plus.
• Wet-lab skills (or knowledge of what a wet-lab looks like) a plus.
• Enthusiasm to learn new techniques. Strong curiosity of areas of biology previously unknown to you.

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.

It is the policy of Ginkgo Bioworks to provide equal employment opportunities to all employees, employment applicants, and EOE disability/vet.