Scientist II, Computational Biology (Single Cell & Spatial)

eGenesis; Cambridge (MA); On-site; USD 130,000 - 180,000; Full time

Job summary

eGenesis is a Cambridge, MA biotech advancing engineered organs. We seek a Scientist II to drive single cell and spatial genomics analyses of engineered organs and immune interactions across translational programs.

You will design analyses, integrate multimodal data, and build scalable pipelines while collaborating with wet labs, immunologists, and clinicians. PhD and 3+ years in the field are required, with strong R/Python skills and experience in spatial transcriptomics.

Qualifications

• PhD in a computational biology, genomics, bioinformatics, immunology, or related field with 3+ years of postdoctoral or industry experience in single cell and spatial data analysis.
• Proven experience leading computational projects from experimental design to interpretation.
• Strong proficiency in R and/or Python for statistics and visualization.
• Deep understanding of immune cell biology and ability to interpret immune-related transcriptional signatures.
• Hands-on experience with spatial transcriptomics platforms (Visium/Visium HD, Xenium, Trekker, Seeker) and cross-platform integration.
• Fluency with standard single cell and spatial analysis tools (Seurat, Scanpy, Cell Ranger, SpatialData, Squidpy).
• Experience using AI tools to accelerate analysis and software development with careful validation.
• Track record of independently defining and answering open research questions, evidenced by first-author publications or equivalent work.

Responsibilities

• Identify and frame open biological questions across programs and set priorities with minimal direction.
• Lead design, analysis, and interpretation of scRNA-seq and spatial transcriptomics experiments.
• Integrate multimodal datasets to uncover tissue remodeling and immune responses.
• Collaborate with wet labs, immunologists, bioinformaticians, clinicians and translational scientists.
• Develop scalable pipelines for high-dimensional datasets and create new analytical approaches as needed.
• Analyze spatially resolved cell states, tissue architecture, and cell-cell interactions related to graft injury and repair.
• Translate questions into computational analyses and testable hypotheses rooted in xenotransplant biology.
• Present findings to stakeholders and contribute to publications and patents.

Skills

R

Python

Single cell analysis

Spatial transcriptomics

Data integration

Immunology knowledge

Cross-platform analysis

AI tools usage

Scientific communication

Education

PhD in Computational Biology / Genomics / Bioinformatics / Immunology

Tools

Seurat

Scanpy

Cell Ranger

SpatialData

Squidpy

Visium

Xenium

Trekker

Seeker

Job description

ABOUT EGENESIS

eGenesis is a clinical-stage biotechnology company developing human-compatible engineered organs to address the severe global organ shortage. The Company’s proprietary genome engineering platform enables extensive, multiplex gene edits to remove key biological barriers, add protective human transgenes, and inactivate endogenous retroviruses. EGEN-2784, a genetically engineered porcine kidney, is the Company’s lead program and is currently being evaluated in a multi-patient Expanded Access study at MGH. eGenesis is headquartered in Cambridge, MA.

At eGenesis, our core values—innovation, collaboration, compassion, resilience, and passion—are at the center of how we work. We engineer hope and bring passion to everything we do. We collaborate and learn from one another, combining diverse expertise to tackle complex challenges. We innovate boldly, pushing boundaries and science to new heights. where no pig organ has gone before. With resilience, we navigate challenges and celebrate progress together. And in all we do, we lead with compassion—for our patients, our people, and our pigs.

Position Summary

We are seeking a highly skilled and motivated Scientist II with expertise in single cell and spatial genomics data analysis. The ideal candidate will play a key role in unraveling the cellular and spatial architecture of engineered organs and immune interactions in our translational research programs. This is a unique opportunity to drive high-impact research at the intersection of genomics, immunology, and synthetic biology.

Primary Responsibilities

• Identify and frame open biological questions across our programs, define the analytical strategy to address them, and set your own priorities with minimal day-to-day direction
• Lead the design, analysis, and interpretation of single cell RNA-seq and spatial transcriptomics experiments
• Integrate multimodal datasets, including spatial transcriptomics, scRNA-seq, proteomics, metabolomics, pathology and clinical metadata, to uncover insights into tissue remodeling and immune responses
• Collaborate with cross-functional teams including wet lab scientists, immunologists, bioinformaticians, clinicians and translational scientists
• Develop scalable pipelines for high-dimensional single cell and spatial datasets, and build new analytical approaches where existing tools fall short (e.g., cross-species cell mapping, sparse or incomplete reference annotations)
• Perform spatially resolved analyses of cell states, tissue architecture, cell-cell interactions, and molecular programs associated with graft injury, inflammation, remodeling, and repair
• Translate biological and translational questions into computational analyses and testable hypotheses, with interpretation grounded in immunological mechanisms and xenotransplant biology
• Present findings to internal stakeholders and contribute to publications and patents

Basic Qualifications

• PhD in Computational Biology, Genomics, Bioinformatics, Immunology, or a related field
• 3+ years of postdoctoral or industry experience analyzing single cell and spatial data, including scRNA-seq and spatial transcriptomics
• Demonstrated experience leading computational projects from experimental design and data QC through biological interpretation and communication of results
• Strong proficiency with R and/or Python for statistical computing and data visualization
• Deep understanding of immune cell biology and ability to interpret immune-related transcriptional signatures
• Hands-on experience analyzing spatial transcriptomics data from at least one sequencing-based or imaging-based platform (e.g., Visium/Visium HD, Xenium, Trekker, Seeker); experience integrating across platforms is a strong plus. Candidate should have an understanding of platform-specific strengths, limitations, and analytical considerations
• Fluency with standard single cell and spatial analysis tools (e.g., Seurat, Scanpy, Cell Ranger, SpatialData, Squidpy)
• Practical experience using AI tools (e.g., LLM-based coding assistants and agents) to speed up analysis and software development, with the judgment to check AI-generated code and results critically
• Track record of independently defining and answering open research questions, where the question, approach, or method was not set in advance, as shown by first-author publications, novel methods, or equivalent industry work

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.