Scientist II Single Cell Computational Biology
Scientist II Single Cell Computational Biology
Posted on :
15-04-2025
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1 Vacancy
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Job 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 highimpact research at the intersection of genomics immunology and synthetic biology.
PRIMARY RESPONSIBILITIES
- Lead the design analysis and interpretation of single cell RNAseq ATACseq and spatial transcriptomics experiments
- Integrate multimodal datasets (e.g. scRNAseq CITEseq spatial transcriptomics) to uncover insights into tissue remodeling and immune responses
- Collaborate with crossfunctional teams including wet lab scientists immunologists bioinformaticians and translational scientists
- Develop and implement scalable pipelines and custom analytical tools for highdimensional 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 (scRNAseq scATACseq 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 immunerelated 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
Employment Type
Full-Time
Key Skills
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