Manifoldbio~1mo ago

Scientist, cDNA Display

Bostonmid

OtherScientist

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Quick Summary

Overview

Key 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…

Requirements Summary

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…

Technical Tools

OtherScientist

Manifold Bio is a platform biotechnology company pioneering AI-guided protein design and massively multiplexed in vivo screening to unlock tissue-targeted medicines and organism-scale models of living systems. Using proprietary molecular barcoding technology, we screen hundreds of thousands of protein designs simultaneously in living systems, producing in vivo-validated datasets at a scale no one else can match. The datasets power our computational models, which leads to better drug designs, creating a flywheel that gets stronger with every campaign. Our team of protein engineers, biologists, and computational scientists works across this full stack to pursue programs both internally and with leading pharma companies.

Responsibilities

~1 min read

→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

Requirements

~1 min read

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

Requirements

~1 min read

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

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

Base Salary Range: $118,000-138,000

This reflects the typical offer range for this role, based on experience, role scope, and internal equity. Final compensation decisions are made using a consistent leveling framework and consider the candidate’s experience, interview performance, and expected impact.

This role is eligible for:

Annual performance-based target bonus
Stock options
Comprehensive medical, dental, and vision coverage
401(k) plan
Flexible paid time off and holidays
Perks including on-site gym, onsite lunch, and commuter support

Our compensation ranges are reviewed annually to ensure alignment with market trends and internal equity.

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.