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