Scientist, cDNA Display

<div class="content-intro"><p><strong>Manifold Bio builds AI models for protein therapeutic design, trained on proprietary experimental data generated at unprecedented scale.</strong> Our <em>in vivo</em>-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.</p></div><p><strong>Position</strong></p> <p><strong>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. </strong>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.</p> <p> </p> <p><strong>Responsibilities</strong></p> <ul> <li>Design, develop, and validate a cell-free display platform (cDNA display or similar) compatible with diverse binder formats </li> <li>Work with automation team to scale and automate the platform to enable routine, high-throughput screening against large panels of therapeutic targets</li> <li>Collaborate with ML and computational teams to ensure screening outputs feed effectively into model training pipelines</li> <li>Work with the protein engineering team to support discovery campaigns and affinity maturation as platform capacity allows </li> <li>Stay current on advances in cell-free display, laboratory automation, and computational protein design</li> </ul> <p> </p> <p><strong>Required Qualifications</strong></p> <ul> <li>PhD or equivalent experience in protein biochemistry, molecular biology, biological engineering, or a related field</li> <li>Hands-on experience with cell-free selection systems (cDNA display, mRNA display, ribosome display, or similar)</li> <li>Strong molecular biology fundamentals and demonstrated ability to develop and troubleshoot complex, multi-step workflows</li> <li>Experience with or strong interest in laboratory automation</li> </ul> <p> </p> <p><strong>Preferred Qualifications</strong></p> <ul> <li>Track record of successfully automating complex laboratory workflows</li> <li>Background in therapeutic antibody discovery or protein engineering </li> <li>Experience with computational protein design</li> <li>Familiarity with how high-throughput screening data feeds into ML and computational pipelines</li> <li>Experience with complex or non-traditional binder formats and biochemical intuition to adapt selection workflows accordingly</li> </ul> <p> </p> <p><strong>Why you might be a good fit</strong></p> <ul> <li>Building systems that generate data at a scale previously impossible excites you</li> <li>You thrive in fast-moving environments where you own a problem end-to-end</li> <li>You are energized by working at the intersection of wet lab science, automation, and AI-driven biotherapeutic discovery</li> <li>You are a collaborative scientist who communicates well across teams with different technical backgrounds</li> </ul><div class="content-conclusion"><p><em style="color: rgb(34, 34, 34); font-family: Arial, Helvetica, sans-serif; font-weight: 400; letter-spacing: normal; text-align: start; white-space: normal; word-spacing: 0px; text-decoration: none;"><em><span style="font-weight: 400;">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.</span></em></em></p></div>