Computational Scientist, Assay Development

Responsibilities

• Invent new quantitative protein engineering assays working with experimental scientists
• Build robust data pipelines with rich metrics and statistics for real-time dataset analysis and reporting
• Perform analysis and "hit calling" support, contributing new insights to active projects
• Improve library design workflows to best co-optimize antibody libraries for enhanced performance
• Write and contribute robust code in shared libraries for common protein design tasks
• Collaborate on designing high-throughput experiments and analyze/interpret results from phage display and yeast display platforms
• Deliver high-quality data reporting through slides and documentation for cross-functional teams

Requirements

• PhD and/or 4+ years of experience in computational biology, bioinformatics, or protein engineering
• Rich experience with Python and data pipeline development
• Strong antibody engineering background with experience in design, optimization, or discovery
• Experience with massively parallel reporter assays (MPRAs) and high-throughput screening data analysis
• Experience designing DNA libraries for binders, DMS, or phage display
• Experience working with Next Generation Sequencing (NGS) data
• Strong understanding of statistics fundamentals and data analysis methodologies

Preferred Qualifications

• Industry experience in antibody therapeutic development or biotechnology R&D
• Track record of developing computational tools or pipelines adopted by experimental teams
• Experience mentoring junior scientists or leading cross-functional project teams
• Familiarity with cloud computing platforms (AWS, GCP) and containerization technologies

About the Company

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.