Scientist II, Computational Biology – Single Cell, Spatial

eGenesis, Inc.

. Identify and frame open biological questions across programs, define analytical strategies, and set priorities with minimal day-to-day direction.

Posted 10/2/2026full-timeCambridge • Massachusetts • United StatesMid-LevelSenior💰 $135,000 - $165,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Expertise in analyzing single cell and spatial transcriptomics data, with strong proficiency in R and Python for statistical computing and data visualization. Ability to integrate multimodal datasets and translate biological questions into computational analyses, while collaborating effectively with cross-functional teams.

Highest-signal resume keywords

Single Cell RNA-Seq AnalysisSpatial TranscriptomicsR ProgrammingPython ProgrammingImmunology Expertise

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data AnalysisStatistical ComputingData VisualizationExperimental DesignData Quality ControlBiological InterpretationComputational BiologyTranslational ResearchCellular Architecture AnalysisImmune Cell Biology

Soft Skills

CollaborationCommunicationIndependent Research

Tools & Technologies

SeuratScanpyCell RangerSpatialDataSquidpyVisiumXeniumTrekkerSeekerAI Tools

Certifications & Qualifications

PhD in Computational BiologyPhD in GenomicsPhD in BioinformaticsPhD in Immunology

Industry Keywords

Multimodal DatasetsTissue RemodelingImmune ResponsesGraft InjuryInflammationRepairTranslational ScienceCell-Cell InteractionsMolecular ProgramsResearch Publications

Tech Stack

Tools & technologies

Python

About the role

Key responsibilities & impact

Identify and frame open biological questions across programs, define analytical strategies, and set 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 wet lab scientists, immunologists, bioinformaticians, clinicians, and translational scientists.
Develop scalable pipelines for high-dimensional single cell and spatial datasets and create new analytical approaches where existing tools are insufficient.
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 grounded in immunological mechanisms and xenotransplant biology.
Present findings to internal stakeholders and contribute to publications and patents.
Analyze the cellular and spatial architecture of engineered organs and immune interactions in translational research programs.

Requirements

What you’ll need

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, such as Visium/Visium HD, Xenium, Trekker, or Seeker.
Understanding of platform-specific strengths, limitations, and analytical considerations; experience integrating across platforms is a strong plus.
Fluency with standard single cell and spatial analysis tools, including Seurat, Scanpy, Cell Ranger, SpatialData, and Squidpy.
Practical experience using AI tools, such as LLM-based coding assistants and agents, to accelerate analysis and software development, with ability to critically check AI-generated code and results.
Track record of independently defining and answering open research questions, demonstrated through first-author publications, novel methods, or equivalent industry work.