Scientist II, Single Cell Computational Biology

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Company: eGenesis, Inc.

Location: Cambridge, MA 02139

Description:

COMPANY MISSION

At eGenesis, we aspire to deliver safe and effective human transplantable cells, tissue and organs utilizing the latest advancements in genome editing.

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
    • Lead the design, analysis, and interpretation of single cell RNA-seq, ATAC-seq, and spatial transcriptomics experiments
    • Integrate multi-modal datasets (e.g., scRNA-seq, CITE-seq, spatial transcriptomics) to uncover insights into tissue remodeling and immune responses
    • Collaborate with cross-functional teams including wet lab scientists, immunologists, bioinformaticians, and translational scientists
    • Develop and implement scalable pipelines and custom analytical tools for high-dimensional single cell datasets
    • Interpret data in the context of immunological mechanisms and xenotransplantation
    • Present findings to internal stakeholders and contribute to publications and patents


BASIC QUALIFICATIONS
    • PhD with 3+ years of experience in Computational Biology, Genomics, Bioinformatics, Immunology, or a related field
    • 2+ years of postdoctoral or industry experience analyzing single cell genomics data (scRNA-seq, scATAC-seq, spatial omics)
    • 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
    • Familiarity with popular single cell analysis tools (e.g., Seurat, Scanpy, Cell Ranger, Loupe, Squidpy, etc.)
    • Demonstrated ability to work independently on complex data analysis problems and communicate results clearly to interdisciplinary teams

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