Scientist, mRNA/cDNA/Cell-Free Display

Manifold Bio

Boston (MA)

On-site

USD 85,000 - 130,000

Full time

14 days+

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Job summary

A biotechnology firm in Boston is seeking a scientist to build an automated cell-free display platform for screening protein binder libraries. The ideal candidate will have a PhD in a relevant field and hands-on experience with cell-free display technologies. Responsibilities include designing and scaling the platform, collaborating with teams on model training, and supporting discovery campaigns. This role is at the intersection of protein engineering, lab automation, and AI-driven drug discovery.

Qualifications

  • Deep expertise in cell-free display technologies.
  • Strong molecular biology fundamentals.
  • Ability to develop and troubleshoot complex workflows.

Responsibilities

  • Design and validate a cell-free display platform suitable for diverse binder formats.
  • Collaborate with automation team to scale automated screening platform.
  • Ensure screening outputs effectively feed into model training pipelines.

Education

PhD or equivalent experience in protein biochemistry, molecular biology, biological engineering, or a related field

Tools

cell-free selection systems (cDNA display, mRNA display, ribosome display)
laboratory automation

Job description

Manifold Bio builds AI models for protein therapeutic design, trained on proprietary experimental data generated at unprecedented scale. Our in vivo-centric discovery platform produces millions of experimentally validated protein designs per campaign, creating the datasets that make our models possible and our approach uniquely powerful. We combine high-throughput protein engineering with computational design to create antibody-like drugs and other biologics. Our world‑class team of protein engineers, biologists, and computational scientists are working together to aim the platform at therapeutic opportunities where precise targeting is the key to overcoming clinical challenges.

Position

Manifold Bio is seeking a scientist to build and own a high‑throughput, automated cell‑free display platform for screening computationally designed protein binder libraries against hundreds of therapeutic receptor targets. This platform will be a cornerstone of Manifold's closed‑loop AI‑driven molecule discovery engine, generating the large‑scale, high‑quality binding data needed to train and improve our design models. The ideal candidate is a hands‑on scientist with deep expertise in cell‑free display technologies and a drive to build automated systems that can operate at scale. You will work at the intersection of protein engineering, laboratory automation, and ML‑guided drug discovery, collaborating closely with our binder discovery, ML, and automation teams.

Responsibilities
  • Design, develop, and validate a cell‑free display platform (cDNA display or similar) compatible with diverse binder formats
  • Work with automation team to scale and automate the platform to enable routine, high‑throughput screening against large panels of therapeutic targets
  • Collaborate with ML and computational teams to ensure screening outputs feed effectively into model training pipelines
  • Work with the protein engineering team to support discovery campaigns and affinity maturation as platform capacity allows
  • Stay current on advances in cell‑free display, laboratory automation, and computational protein design
Required Qualifications
  • PhD or equivalent experience in protein biochemistry, molecular biology, biological engineering, or a related field
  • Hands‑on experience with cell‑free selection systems (cDNA display, mRNA display, ribosome display, or similar)
  • Strong molecular biology fundamentals and demonstrated ability to develop and troubleshoot complex, multi‑step workflows
  • Experience with or strong interest in laboratory automation
Preferred Qualifications
  • Track record of successfully automating complex laboratory workflows
  • Background in therapeutic antibody discovery or protein engineering
  • Experience with computational protein design
  • Familiarity with how high‑throughput screening data feeds into ML and computational pipelines
  • Experience with complex or non‑traditional binder formats and biochemical intuition to adapt selection workflows accordingly
Why you might be a good fit
  • Building systems that generate data at a scale previously impossible excites you
  • You thrive in fast‑moving environments where you own a problem end‑to‑end
  • You are energized by working at the intersection of wet lab science, automation, and AI‑driven biotherapeutic discovery
  • You are a collaborative scientist who communicates well across teams with different technical backgrounds

We value different experiences and ways of thinking and believe the most talented teams are built by bringing together people of diverse cultures, genders, and backgrounds.

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