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.

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

Strong understanding of statistics fundamentals and data analysis methodologies

Rich experience with Python, agentic coding, data pipeline development

Familiarity with version control, test-driven development, and Unix computing

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

Outstanding written and verbal communication skills for cross-functional collaboration

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

Publications or patents in antibody engineering, protein design, or high-throughput screening methods

Familiarity with cloud computing platforms (AWS, GCP).

Strong antibody engineering background with first-hand experience in antibody design, optimization, or discovery

This Role Might Be Perfect For You If

You thrive in collaborative environments where computational insights directly guide experimental decisions

You're 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

You're 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: $118,000-138,000

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 candidate’s 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 you’re excited to build a platform that combines these technologies to revolutionize how protein therapeutic discovery happens, please reach out to careers@manifold.bio.

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.