Jobs at Manifold Bio

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.

• 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

• 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