Staff Scientist, Protein Science (Computational)

Pacific Biosciences • Menlo Park, CA

1d • Onsite

About The Position

Staff Scientist, Protein Science (Computational) PacBio (NASDAQ: PACB) is a premier life science technology company that designs, develops, and manufactures advanced sequencing solutions to help scientists and clinical researchers resolve genetically complex problems. Our mission is to enable the promise of genomics to better human health. Genomics is core to all biological processes, and our advanced genomics tools provide scientists and clinical researchers the insights to better understand biology and health. We are now entering the century of biology and genomics is at the heart of the next revolution. Become part of the new paradigm in gene sequencing and help shape the future of genomic study by joining the PacBio team. We have an opening for a computational protein engineer to drive projects that strongly impact the performance of PacBio’s long read sequencing platforms. This high-visibility role provides an opportunity to lead early- to mid-stage protein engineering efforts from ideation through lead candidate optimization and to support late-stage development to ensure our products provide best-in-class long read NGS performance. The successful candidate will excel at managing multiple projects, working closely with experimental teams to design variants, interpret experimental data, and guide iteration cycles to meet defined product goals. A second core focus of this role is to stay current with advances in in silico methods for protein engineering. You will pilot new in silico methods to determine their practical value, with an expectation of identifying and working collaboratively to integrate approaches that meaningfully improve prediction, throughput, and design success. We encourage candidates of all backgrounds and experiences to apply, including those who may not meet every requirement but are excited about the opportunity to contribute to our mission and can provide a competitive advantage in other aspects of the role.

Requirements

• Deep experience with one or more established in silico protein optimization tools ( e.g., Rosetta Commons) and familiarity with recent and emerging tools ( e.g., ProteinMPNN, AlphaFold, Boltz, ESM).
• Strong mechanistic understanding of polymerases, transposases, reverse transcriptases, and/or other DNA-interacting proteins.
• Experience combining in silico tools with rigorous experimental validation (independent or collaborative).
• Familiarity with techniques in biochemical and/or biophysical enzyme characterization.
• Working knowledge of next-generation sequencing (NGS) workflows and enzyme requirements within those systems.
• Demonstrated ability to translate experimental results into actionable insights for research or product development programs.
• Experience leading cross-functional projects in a highly collaborative environment.
• Strong communication skills for presenting technical data to diverse audiences.
• PhD in Bioinformatics, Structural Biology, Computational Biology, or related field (or equivalent experience) with 5 to 10+ years of combined industry and post-doctoral experience in protein engineering.
• Proficiency in Linux-based environments, scripting languages such as Python or R, and experience working with HPC or cloud-based computing.
• Track record of strong scientific contributions ( e.g., product and/or technology development, high-impact publications, or other product-relevant outputs).
• Candidates must have current authorization to work in the United States without the need for present or future sponsorship.

Nice To Haves

• Experience leading collaborative projects in multidisciplinary environments supporting product development is preferred.

Responsibilities

• Work collaboratively to optimize sequencing chemistries through enzyme and substrate engineering.
• Translate project and product goals into engineering strategies and lead design–build–test–learn cycles of screening and data analysis.
• Serve as a subject matter expert in product development programs, providing deep technical insights by integrating experimental data, in silico modeling, and literature findings.
• Contribute to program execution by identifying risks, proposing mitigations, and adapting plans based on emerging data.
• Maintain strong collaborations across departments and functions, including biochemistry, chemistry, and software development to advance new technology development opportunities.
• Foster a culture of high scientific rigor, mutual respect, and transparency in knowledge and data sharing.
• Maintain a strong understanding of sequencing workflows and relevant biochemical systems to inform experimental design.
• Communicate findings through internal presentations, reports, and contributions to publications or external presentations as appropriate.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: Ph.D. or professional degree