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Digital Biology

Senior Scientist, High-Throughput Protein Binder Screening

Watertown, Massachusetts, United States

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hirly's read of this role

Seniority
Senior
Country
US
Work mode
On-site / unstated
First seen by hirly
17 Oct 2026

Derived automatically from the posting. Upload your resume above to see how the role scores against it.

the posting

Senior Scientist, High-Throughput Protein Binder Screening

Location: Watertown, MA

Employment Type: Full-time, on-site

Reports to: CSO

Direct reports: Research Associates, High-Throughput Protein Binder Screening

About Digital Biology

Digital Biology is the data lab for AI protein drug engineering, building a measurement-driven discovery engine for next-generation biologics. We combine high-throughput experimental systems, advanced molecular technologies, automation, and computational modeling to generate biological data at unprecedented scale and resolution.

Our team works across protein engineering, functional screening, spatial biology, and AI-guided drug discovery. We partner with leading biotechnology and pharmaceutical organizations to build training and validation datasets that enable the design of better therapeutic proteins.

The Position

Digital Biology is hiring a Senior Scientist to lead our partnered high-throughput protein binder screening operation.

We are looking for an expert in protein library methods and molecular cloning who champions process: standardized protocols, robust SOPs, and well-trained teams. You will also stay hands-on, optimizing protocols and supporting successful operation of the workflow end to end, from library construction through analysis and QC.

In this role, you will have the opportunity to grow a team screening millions of proteins per month, and to interface directly with our partners in defining data goals and delivering quality data.

Responsibilities

Lead research associates running high-throughput screening campaigns at a scale of millions of proteins per month.

Own the core workflow end to end: DNA library cloning, production, selection, NGS preparation, analysis, and QC.

Establish SOPs, standardized protocols, and training materials.

Optimize protocols hands-on to improve robustness, throughput, cost, and turnaround, leveraging lab automation to scale and maintain consistency.

Set QC metrics and acceptance criteria, and sign off on data.

Work closely with computational scientists to close the loop, reporting progress and risks to the team and partners.

Qualifications

5+ years of industry experience running high-throughput assays; PhD in molecular biology, protein biochemistry, or a related field preferred

Expert in molecular cloning, with hands-on experience building DNA libraries

Experience running display campaigns (e.g. phage, yeast, mammalian)

Working knowledge of NGS library preparation and sequencing-based analysis and QC

A track record of writing SOPs, standardizing workflows, and training teams to run them reliably

Experience managing research associates or scientists; automated liquid handling a plus

What We Offer

The ability to generate and validate protein binding data at scale on one of the most capable experimental screening platforms

A chance to shape the data foundations behind AI-driven protein and antibody design

Close collaboration with experts in protein engineering, laboratory automation, and computational biology

An ambitious team solving hard problems at the intersection of hard tech, biology, and ML.

Highly competitive salary, equity, and benefits package

Digital Biology is an equal-opportunity employer. We value different experiences, perspectives, and ways of thinking, and we believe the strongest scientific teams are built by bringing together people with diverse backgrounds and expertise.

Company Benefits: Health, vision, life, dental insurance and 401K plan.

If you don't meet all of the requirements listed here, we still encourage you to apply or reach out to us. No job description is perfect – we may find an even more suitable opportunity that is a better fit for you.

Original posting on Digital Biology's site ↗

Listed on hirly, a job board. hirly is not the employer: Digital Biology is hiring for this role.

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