Computational Scientist, Protein Engineering

Position

Manifold 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.

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 (biopanning phi-seq in vivo) and yeast display platforms
• Deliver high-quality data reporting through slides and documentation for cross-functional teams
• Proactively share findings with colleagues through excellent documentation and discussions

Required Qualifications

• PhD and/or 4 years of equivalent experience in computational biology bioinformatics protein engineering antibody engineering or similar field working with biological sequences
• Rich experience with Python agentic coding data pipeline development
• Familiarity with version control test-driven development and Unix computing
• Strong antibody engineering background with first-hand experience in antibody design optimization or discovery
• Experience with massively parallel reporter assays (MPRAs) and high-throughput screening data analysis
• Experience designing DNA libraries for binders DMS phage display or equivalent high-throughput experiments
• Experience working with Next Generation Sequencing (NGS) data from library-based experiments
• Strong understanding of statistics fundamentals and data analysis methodologies
• Outstanding written and verbal communication skills for cross-functional collaboration

Preferred Qualifications

• Intuition or exposure to best practices in software/data engineering
• 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
• Publications or patents in antibody engineering protein design or high-throughput screening methods
• Familiarity with cloud computing platforms (AWS GCP) and containerization technologies

This Role Might Be Perfect For You If

• You thrive in collaborative environments where computational insights directly guide experimental decisions
• Youre energized by translating complex datasets into actionable recommendations for drug discovery teams
• You enjoy building robust production-quality tools that others rely on for critical decisions
• Youre passionate about the therapeutic potential of engineered antibodies and want to accelerate their development
• You love working at the intersection of cutting-edge computational methods and innovative experimental platforms

Base Salary Range: $00

This 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 candidates experience interview performance and expected impact.

This role is eligible for:

• Annual performance-based target bonus
• Stock options
• Comprehensive medical dental and vision coverage
• 401(k) plan
• Flexible paid time off and holidays
• Perks including on-site gym onsite lunch and commuter support

Our compensation ranges are reviewed annually to ensure alignment with market trends and internal equity.

If youre excited to build a platform that combines these technologies to revolutionize how protein therapeutic discovery happens please reach out to

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.