Digital Biology logo

Senior Research Associate, High-Throughput Protein Binder Screening

Digital Biology

Watertown, MAFull-timePosted 1w agoStill listed 2 days ago

Most applications go out cold — see where you stand first. No sign-up to start.

Watch jobs like this.

At a glance

Compensation
No compensation found
Location
Watertown, MA
Role Type
Research
Schedule
Full-time
Work Authorization
Not specified

Olive lists jobs from US employers, including remote roles you can work from the United States.

Requirements

Credentials this posting asks for.

Bachelor's degree

Job overview

Digital Biology seeks a Senior Research Associate to execute and scale high‑throughput protein binder screening campaigns, operating core experimental workflows for external partners and delivering reproducible, decision‑quality data for AI‑guided drug discovery.

Skills & qualifications

RequiredNice to have

Skills

Protein BiochemistryMolecular BiologyBiological EngineeringHigh‑Throughput AssaysLaboratory AutomationPhage DisplayYeast DisplayHigh‑Throughput CloningLibrary Preparation for NGSAutomated Liquid HandlersDocumentationSample TraceabilityData Structuring

Qualifications

Bachelor's in Relevant Field or EquivalentIndustry Experience With High‑Throughput AssaysDemonstrated Ability to Execute and Troubleshoot Complex Multi‑Step WorkflowsExperience With Laboratory Automation

Benefits

Medical Insurance
Dental Insurance
Vision Insurance
401(k) Match

Full job description

Job Title: Senior Research Associate, High-Throughput Protein Binder Screening Location: Watertown, MA Employment Type: Full-time, on-site 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 seeking a Senior Research Associate to execute and scale high-throughput protein binder screening campaigns. You will operate a core experimental workflow for external partners developing world-leading AI protein-design models, generating the large, consistent, and information-rich datasets required to train and improve those systems. This is a highly hands-on role for a scientist who is excellent at executing scaled, multi-step assays with precision and throughput. You will be responsible for running binder-selection campaigns across large libraries and target panels, measuring assay performance, and ensuring that every campaign produces reproducible, decision-quality data. You will work closely with protein engineers, molecular biologists, automation engineers, and computational scientists. The ideal candidate combines strong experimental discipline with the curiosity and initiative to continually make workflows more reliable, faster, and more scalable. Responsibilities

  • Execute end-to-end, high-throughput display campaigns, including library preparation, production, selection, amplification, and sequencing preparation
  • Manage concurrent partner campaigns against defined timelines, quality standards, and deliverables
  • Optimize key steps within complex workflows and improve throughput, reproducibility, cost, and turnaround time
  • Maintain rigorous documentation, sample traceability, and standardized procedures
  • Collaborate with computational teams to structure experimental data and metadata for downstream analysis
  • Partner with automation engineers to optimize robotic liquid-handling workflows
  • Communicate campaign progress, results, risks, and recommendations to stakeholders

Required Qualifications

  • BS, MS, or equivalent experience in protein biochemistry, molecular biology, biological engineering, or a related field
  • Industry experience with high-throughput assays and strong molecular biology fundamentals
  • Demonstrated ability to execute and troubleshoot complex, multi-step workflows
  • Experience with or strong interest in laboratory automation

Preferred Qualifications

  • Direct experience with phage display or yeast display.
  • High-throughput cloning and/or library experience.
  • Experience with library preparation for NGS.
  • Experience operating or developing workflows for automated liquid handlers.

Why You Might Be a Good Fit

  • You are energized by ambitious, high-throughput experiments where execution quality directly determines the value of the data.
  • You take ownership of complex workflows, proactively troubleshooting and improving their reproducibility, efficiency, and scale.
  • You thrive in a fast-moving, collaborative environment and communicate effectively across scientific, computational, and engineering teams.

What We Offer

  • The opportunity to help build a high-throughput experimental platform at the intersection of protein engineering, automation, and AI
  • Meaningful ownership of programs conducted with leading biotechnology and pharmaceutical partners
  • Competitive salary and equity compensation
  • Comprehensive medical, dental, and vision coverage
  • Flexible paid time off and company holidays
  • A collaborative, ambitious team

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.

Similar jobs, posted recently

Open roles like this one, listed in the last 30 days.

You've read the whole posting — now see how you match it.