Computational Scientist, Assay Development

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.PositionManifold Bio is seeking an exceptional Computational Scientist to join our growing Quantitative Biology team. You will work closely with experimental scientists to design and analyze highly multiplexed protein library experiments. You will specifically be working with traditional phage and yeast display readouts, as well as other proprietary display data. You will be expected to own and independently advance projects in areas related to your deep expertise such as protein design, DNA library design, or machine learning/biophysical modeling from MPRA data. You will work closely with our Head of Platform and our other computational scientists to onboard new capabilities that advance the M-Design platform for data-driven engineering of drugs with desired properties.ResponsibilitiesInvent new quantitative protein engineering assays working with experimental scientistsBuild robust data pipelines with rich metrics and statistics for real-time dataset analysis and reportingPerform analysis and "hit calling" support, contributing new insights to active projectsImprove library design workflows to best co-optimize antibody libraries for enhanced performanceWrite and contribute robust code in shared libraries for common protein design tasksCollaborate on designing high-throughput experiments and analyze/interpret results from phage display (biopanning, phi-seq, in vivo) and yeast display platformsDeliver high-quality data reporting through slides and documentation for cross-functional teamsProactively share findings with colleagues through excellent documentation and discussionsRequired QualificationsPhD and/or 4+ years of equivalent experience in computational biology, bioinformatics, protein engineering, antibody engineering, or similar field working with biological sequencesStrong understanding of statistics fundamentals and data analysis methodologiesRich experience with Python, agentic coding, data pipeline developmentFamiliarity with version control, test-driven development, and Unix computingExperience with massively parallel reporter assays (MPRAs) and high-throughput screening data analysisExperience designing DNA libraries for binders, DMS, phage display, or equivalent high-throughput experimentsExperience working with Next Generation Sequencing (NGS) data from library-based experimentsOutstanding written and verbal communication skills for cross-functional collaborationPreferred QualificationsIndustry experience in antibody therapeutic development or biotechnology R&DTrack record of developing computational tools or pipelines adopted by experimental teamsExperience mentoring junior scientists or leading cross-functional project teamsPublications or patents in antibody engineering, protein design, or high-throughput screening methodsFamiliarity with cloud computing platforms (AWS, GCP).Strong antibody engineering background with first-hand experience in antibody design, optimization, or discoveryThis Role Might Be Perfect For You IfYou thrive in collaborative environments where computational insights directly guide experimental decisionsYou're energized by translating complex datasets into actionable recommendations for drug discovery teamsYou enjoy building robust, production-quality tools that others rely on for critical decisionsYou're passionate about the therapeutic potential of engineered antibodies and want to accelerate their developmentYou love working at the intersection of cutting-edge computational methods and innovative experimental platformsBase Salary Range: $118,000-138,000This 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 bonusStock optionsComprehensive medical, dental, and vision coverage401(k) planFlexible paid time off and holidaysPerks including on-site gym, onsite lunch, and commuter supportOur compensation ranges are reviewed annually to ensure alignment with market trends and internal equity.If you’re excited to build a platform that combines these technologies to revolutionize how protein therapeutic discovery happens, please reach out to View email address on click.appcast.io 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.