---
title: 'Computational Scientist, Assay Development at Manifold Bio'
canonical: 'https://feeny.ai/job/computational-scientist-assay-development-manifold-bio-boston-4qvj0atdygfs'
type: 'job'
last_seen: '2026-09-13'
---

# Computational Scientist, Assay Development at Manifold Bio

- **Company:** Manifold Bio
- **Location:** Boston, MA
- **Posted:** 2026-05-04
- **Last confirmed live:** 2026-09-13
- **Apply:** https://job-boards.greenhouse.io/manifoldbio/jobs/5127570007

## Job description

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.

## About Manifold Bio

## Company Overview
- **One-liner**: Manifold Bio is a platform therapeutics company building the first AI-guided direct-to-vivo discovery platform to design tissue-targeted biologics.
- **Entity Type**: Private (Series A)
- **Headquarters**: Boston, Massachusetts, United States
- **Founded**: 2019
- **Founders**: Gleb Kuznetsov (CEO), Pierce Ogden (CTO), Shane Lofgren (Head of Business Development)

## Core Business
- **Primary industries**: Biotechnology, Drug Discovery, Artificial Intelligence for Protein Design
- **Target customers**: B2B – large pharmaceutical companies (via partnerships and collaborations) and internal pipeline for novel therapeutics
- **Mission or purpose statement**: “Tissue-targeted medicines, designed in vivo” – building a predictive model of living systems to enable rational design of biologics that precisely reach intended tissues.

## Products & Services
- **mDesign Engine**: Integrated platform combining AI-guided protein design with massively multiplexed in vivo screening to measure pharmacokinetics, biodistribution, and target engagement directly in living systems.
- **mCodes**: Multiplexed protein barcodes decoded via NGS, enabling high-throughput tracking of millions of protein variants in a single experiment.
- **mShuttle Portfolio**: Modular library of brain shuttles engineered and optimized in vivo to deliver payloads across the blood-brain barrier with high specificity and exposure.
- **mBER**: Open-sourced AI model for designing epitope-specific antibodies, validated in million-scale experiments. (SaaS/model, not a product per se)
- **Internal Pipeline**: Tissue-targeted biologic candidates for Alzheimer’s disease, Parkinson’s disease, rare CNS diseases, and cardiometabolic disease.

## Market Standing
- **Valuation/Market Cap**: Not publicly disclosed
- **Total Funding**: $78.18M (CBInsights) / $61.4M (Apollo.io) – conflicting reports; latest available data shows multiple rounds including a $15M Series A in April 2024.
- **Notable Investors/Partners**: Playground Global, Fifty Years, Amazon Web Services, and a strategic collaboration with Roche announced in November 2025.
- **Growth Signals**: Headcount grew 58.1% YoY to 54 employees; published a joint study with NVIDIA validating million-scale AI-driven protein binder design; active job postings up 100% monthly.

## Competitive Advantages
- **Direct-to-vivo platform**: Unlike most AI-driven drug discovery companies that rely on in vitro data, Manifold tests protein designs directly in living systems, capturing physiologically relevant properties like PK, biodistribution, and toxicity.
- **Massively multiplexed experimentation**: Proprietary molecular tracking (mCodes) enables simultaneous testing of millions of protein variants against hundreds of targets, closing the loop between generative AI design and experimental validation at scale.
- **High-profile collaborations**: The Roche partnership and NVIDIA validation provide external credibility and access to industry-leading resources.

## Strategic Focus
- **Expanding tissue-specific delivery**: Starting with brain (CNS) through mShuttle, then moving to peripheral tissues (adipose, cardiometabolic).
- **Building the “virtual organism”**: Integrating high-throughput in vivo data to train a predictive model of how biomolecules behave in the body, enabling fully rational design.
- **Deepening pharma partnerships**: Leveraging platform capabilities to co-develop next-generation biologics with partners like Roche.
- **Open-sourcing AI models**: Releasing mBER and other tools to attract talent, drive adoption, and set industry standards.

## Why Work Here
- **Culture**: Flat, science-driven organization where ML engineers, computational biologists, and wet-lab scientists collaborate closely. Emphasis on “hybrid computational/wet lab science” and library-guided design.
- **Growth trajectory**: 58% employee growth YoY, active hiring across AI/ML, protein engineering, biology, and operations – signals rapid scaling.
- **Work environment**: Boston-based (Seaport area), likely office-first with some flexibility; job postings don’t mention remote but roles are Boston-listed.
- **Notable perks**: Opportunity to work at the frontier of AI + biology, access to cutting-edge wet lab infrastructure, and direct impact on pipeline decisions from early discovery through IND-enabling studies.

## Sources
1. [manifold.bio](https://www.manifold.bio/) (Company website)
2. [linkedin.com](https://www.linkedin.com/company/manifold-bio) (LinkedIn company page)
3. [cbinsights.com](https://www.cbinsights.com/company/manifold-bio) (CBInsights profile)
4. [boards.greenhouse.io](http://job-boards.greenhouse.io/manifoldbio) (Careers page)
5. [manifold.bio/news](https://www.manifold.bio/news) (News – Roche collaboration, NVIDIA study)
6. [apollo.io](https://www.apollo.io/companies/Manifold-Bio) (Apollo.io revenue/funding data)

## Other roles at Manifold Bio

- [Senior Lab Operations Associate](https://feeny.ai/job/senior-lab-operations-associate-manifold-bio-boston-9hzaxy9hgc0z) — Boston, MA
- [Scientist II/Senior Scientist, Protein Sciences – Cell Binding Assays](https://feeny.ai/job/scientist-ii-senior-scientist-protein-sciences-cell-binding-assays-manifold-bio-he5xybzbd1mk) — Boston, MA
- [Scientist, Bioconjugation](https://feeny.ai/job/scientist-bioconjugation-manifold-bio-boston-v1hw9b634cb4) — Boston, MA
- [Research Associate / Senior Research Associate, In Vitro Pharmacology](https://feeny.ai/job/research-associate-senior-research-associate-in-vitro-pharmacology-manifold-bio-a5vxzqjbgfkm) — Boston, MA
- [Associate Scientist/Senior Associate Scientist, In Vivo Pharmacology – Study Coordinator](https://feeny.ai/job/associate-scientist-senior-associate-scientist-in-vivo-pharmacology-study-vs7tg31p2che) — Boston, MA
- [Product Manager, AI Platform & Partnerships](https://feeny.ai/job/product-manager-ai-platform-partnerships-manifold-bio-boston-pghg83twvq9t) — Boston, MA / San Francisco, CA
- [Sr. Director/VP, Biology](https://feeny.ai/job/sr-director-vp-biology-manifold-bio-boston-f5c0ac39wzn7) — Boston, MA
- [AI/ML Scientist, Protein Foundation Models](https://feeny.ai/job/ai-ml-scientist-protein-foundation-models-manifold-bio-boston-ma-or-san-ndnwdy540hyp) — Boston MA OR San Francisco, CA
- [Senior Director, Biotherapeutics](https://feeny.ai/job/senior-director-biotherapeutics-manifold-bio-boston-s6aww0xdkqqd) — Boston, MA
- [AI/ML Research Engineer](https://feeny.ai/job/ai-ml-research-engineer-manifold-bio-boston-ma-or-san-francisco-0qe65tmrvvjb) — Boston MA OR San Francisco, CA