PositionManifold 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 Manifolds 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