Senior Bioinformatics Scientist

Cellular Intelligence
Location
Boston
Job Type
Full-time
Posted
November 8, 2026
Salary Range
$160k - $190k USD

Job Description

About Cellular Intelligence

Cellular Intelligence is building a universal foundation model for cell signaling to understand, predict, and ultimately control how cells behave, transforming biology from trial and error into an engineering discipline. A clinical-stage AI company, Cellular Intelligence holds the global rights to STEM-PD, an investigational Phase 2-ready cell therapy for Parkinson's disease with FDA Fast Track designation, acquired from Novo Nordisk. The company's founding team includes repeat AI entrepreneur Micha Breakstone, Ph.D. (Chorus.ai, acquired for $575M), the Head of the Fundamental AI Group at MIT, and five professors from Harvard Medical School, the University of Pennsylvania, and the University of Washington, collectively holding five National Academy memberships. Based in Boston, Cellular Intelligence has raised over $70M from Khosla Ventures, the Chan Zuckerberg Initiative, Novo Nordisk, AMD Ventures, and others.

Cellular Intelligence’s Core Values

  • We show up - fully accountable, all-in, doing whatever it takes.
  • We act with urgency - swift, decisive, proactive.
  • We support one another - collaborative, helpful, empathetic.

Location: Boston, MA

Reports to: Director of Bioinformatics

About the Role

We seek a Senior Bioinformatics Scientist to own and develop the methods and pipelines that power our proprietary capsule platform and feed our Universal Virtual Cell-Signaling Model. Working across single-cell, spatial, and bulk RNA-seq, you'll build reproducible pipelines, develop new bioinformatics methods, and apply them to our data. You'll collaborate closely with wet lab scientists, software engineers, and machine learning researchers to advance novel sequencing protocols and our therapeutic programs. This is a hands-on role spanning single-cell and spatial omics, ideal for someone who thrives in a fast-paced, interdisciplinary environment and wants to help build our cell-replacement therapy platform from the ground up.

Responsibilities

  • Develop new bioinformatics methods for single-cell, spatial, and bulk transcriptomics data, and adapt and benchmark existing ones.
  • Build and maintain reproducible analysis pipelines for single-cell, spatial, and bulk RNA-seq, from QC and normalization through the downstream analysis appropriate to each modality (integration, clustering, annotation, differential expression).
  • Analyze large-scale single-cell and spatial transcriptomics data, from raw output through to biological interpretation, including visualization of spatial data.
  • Partner with wet-lab scientists to bring novel multi-omic assays online, developing the analysis methods and pipelines that new experimental modalities require.
  • Collaborate with wet-lab and computational scientists to design experiments and interpret results.
  • Provide technical guidance and mentorship across the bioinformatics, ML, and engineering teams, including code and method reviews.

Qualifications

  • PhD in Bioinformatics, Genomics, Computational Biology, Computer Science, or a related field. Equivalent industry experience is also welcome.
  • 3+ years of experience developing, adapting, and benchmarking bioinformatics methods and building reproducible pipelines for large-scale single-cell and/or spatial transcriptomic data.
  • Hands-on experience with single-cell transcriptomics analysis.
  • Strong Python and/or R programming skills.
  • Experience building reproducible workflows with a pipeline manager (e.g. Nextflow or Snakemake), containers, and version control.
  • Experience applying state-of-the-art large language models (LLMs) to bioinformatics projects.
  • Excellent organizational and documentation habits.

Prefered Qualifications

  • Experience with spatial transcriptomics data analysis and visualization.
  • Experience applying and improving automated cell type annotation methods (e.g. marker-based and reference-based methods).

About Cellular Intelligence

Cellular Intelligence is building a universal foundation model for cell signaling to understand, predict, and ultimately control how cells behave, transforming biology from trial and error into an engineering discipline. A clinical-stage AI company, Cellular Intelligence holds the global rights to STEM-PD, an investigational Phase 2-ready cell therapy for Parkinson's disease with FDA Fast Track designation, acquired from Novo Nordisk. The company's founding team includes repeat AI entrepreneur Micha Breakstone, Ph.D. (Chorus.ai, acquired for $575M), the Head of the Fundamental AI Group at MIT, and five professors from Harvard Medical School, the University of Pennsylvania, and the University of Washington, collectively holding five National Academy memberships. Based in Boston, Cellular Intelligence has raised over $70M from Khosla Ventures, the Chan Zuckerberg Initiative, Novo Nordisk, AMD Ventures, and others.

Cellular Intelligence’s Core Values

  • We show up - fully accountable, all-in, doing whatever it takes.
  • We act with urgency - swift, decisive, proactive.
  • We support one another - collaborative, helpful, empathetic.

Location: Boston, MA

Reports to: Director of Bioinformatics

About the Role

We seek a Senior Bioinformatics Scientist to own and develop the methods and pipelines that power our proprietary capsule platform and feed our Universal Virtual Cell-Signaling Model. Working across single-cell, spatial, and bulk RNA-seq, you'll build reproducible pipelines, develop new bioinformatics methods, and apply them to our data. You'll collaborate closely with wet lab scientists, software engineers, and machine learning researchers to advance novel sequencing protocols and our therapeutic programs. This is a hands-on role spanning single-cell and spatial omics, ideal for someone who thrives in a fast-paced, interdisciplinary environment and wants to help build our cell-replacement therapy platform from the ground up.

Responsibilities

  • Develop new bioinformatics methods for single-cell, spatial, and bulk transcriptomics data, and adapt and benchmark existing ones.
  • Build and maintain reproducible analysis pipelines for single-cell, spatial, and bulk RNA-seq, from QC and normalization through the downstream analysis appropriate to each modality (integration, clustering, annotation, differential expression).
  • Analyze large-scale single-cell and spatial transcriptomics data, from raw output through to biological interpretation, including visualization of spatial data.
  • Partner with wet-lab scientists to bring novel multi-omic assays online, developing the analysis methods and pipelines that new experimental modalities require.
  • Collaborate with wet-lab and computational scientists to design experiments and interpret results.
  • Provide technical guidance and mentorship across the bioinformatics, ML, and engineering teams, including code and method reviews.

Qualifications

  • PhD in Bioinformatics, Genomics, Computational Biology, Computer Science, or a related field. Equivalent industry experience is also welcome.
  • 3+ years of experience developing, adapting, and benchmarking bioinformatics methods and building reproducible pipelines for large-scale single-cell and/or spatial transcriptomic data.
  • Hands-on experience with single-cell transcriptomics analysis.
  • Strong Python and/or R programming skills.
  • Experience building reproducible workflows with a pipeline manager (e.g. Nextflow or Snakemake), containers, and version control.
  • Experience applying state-of-the-art large language models (LLMs) to bioinformatics projects.
  • Excellent organizational and documentation habits.

Prefered Qualifications

  • Experience with spatial transcriptomics data analysis and visualization.
  • Experience applying and improving automated cell type annotation methods (e.g. marker-based and reference-based methods).
  • Experience working at the interface of technology development and data analysis, particularly involving novel molecular biology or sequencing techniques.
  • Strong domain knowledge in developmental biology or stem cell research.
  • Experience mentoring scientists or reviewing scientific code.
  • Prior experience in a startup or fast-paced, interdisciplinary environment.

Cellular Intelligence is committed to creating a diverse and inclusive workplace. We welcome and encourage applicants from all backgrounds, regardless of race, ethnicity, gender, sexual orientation, religion, disability, or age. We embrace differences and believe that a diverse workforce enhances our creativity, innovation, and overall success.

Frequently Asked Questions

Where is this job located, and is it remote, hybrid, or on-site?
The role is based in Boston, MA, where Cellular Intelligence is headquartered. The posting does not specify whether the position is remote, hybrid, or on-site.
What qualifications and experience do I need?
You need a PhD in Bioinformatics, Genomics, Computational Biology, Computer Science, or a related field, or equivalent industry experience. You also need 3+ years developing and benchmarking bioinformatics methods and building reproducible pipelines for large-scale single-cell and/or spatial data. Required skills include strong Python and/or R, Nextflow or Snakemake, containers, version control, and experience applying LLMs.
What are the main responsibilities of this role?
You will develop and benchmark bioinformatics methods for single-cell, spatial, and bulk transcriptomics, and build reproducible RNA-seq pipelines. You will analyze large-scale data through to biological interpretation and help bring new multi-omic assays online with wet-lab scientists. You will also collaborate on experiment design and mentor across the bioinformatics, ML, and engineering teams.
Who would I report to, and who would I work with?
You would report to the Director of Bioinformatics. You would collaborate closely with wet-lab scientists, software engineers, and machine learning researchers.
What preferred qualifications would strengthen my application?
Preferred qualifications include spatial transcriptomics analysis and visualization, and automated cell type annotation methods. Also valued are experience with novel molecular biology or sequencing techniques, and developmental or stem cell biology knowledge. Mentoring or scientific code review experience and prior startup or interdisciplinary work also help.

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Job Information

Source: manual
AI Relevance: 95/100 (Highly relevant)
Remote Type: onsite
Skills & Tags:
cellular intelligence machine learning bioinformatics computational biology genomics single-cell clinical transcriptomics LLM

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