Bioinformatician II- Immunology and Immunotherapy

Mount Sinai Health SystemNew York, NY
1d

About The Position

The Laboratory of Tissue Immunity and Regeneration at the Icahn School of Medicine at Mount Sinai is seeking a highly qualified and motivated Bioinformatician II to support computational and analytical research efforts across a diverse portfolio of sequencing- and omics-based studies. The laboratory uses state-of-the-art genomic technologies, including bulk RNA sequencing, bulk ATAC sequencing, single-cell RNA sequencing, single-cell Multiome, and Spatial Transcriptomics/Visium HD, to investigate fundamental and translational questions in tissue immunity, inflammatory memory, regeneration, and inflammatory diseases of the skin and gut. The Bioinformatician II will serve as an integral member of the research team and a key computational partner to experimental investigators. This individual will be responsible for the design, execution, and interpretation of bioinformatic analyses across multiple projects, and will contribute to the development of reproducible analytical workflows and publication-quality scientific outputs. The position requires a high level of technical expertise, strong organizational skills, and the ability to work effectively in a collaborative, fast-paced academic research environment.

Requirements

  • M.S. in Bioinformatics, Biomedical Informatics, Computational Biology, or Genomics. Alternately, M.S. in a discipline requiring strong computational and analytical skills supplemented with some biology exposure. Ph.D in a related field preferred. Those with a Bachelors degree and additional post-graduate experience are considered.
  • 2+ years post-graduate experience in a research environment, including the manipulation of large biological datasets.
  • Advanced knowledge of genetics and/or statistical analysis software and online resources.
  • Experience in programming environments such as MatLab, R statistical package, BioConductor, Perl and C++.

Nice To Haves

  • Prior experience analyzing bulk RNA-seq, bulk ATAC-seq, scRNA-seq, single-cell Multiome, and Spatial Transcriptomics/Visium HD data.
  • Familiarity with single-cell analysis frameworks and data structures, including Seurat and AnnData.
  • Experience developing and maintaining bioinformatics pipelines for sequencing-based workflows.
  • Demonstrated ability to independently perform analyses from raw data processing through downstream interpretation.
  • Experience working in a highly collaborative laboratory or translational research environment.
  • Strong written and verbal scientific communication skills, including experience preparing publication-quality figures and analyses.
  • Interest in inflammatory disease biology, tissue immunology, regeneration, and translational team science.

Responsibilities

  • Conduct end-to-end computational analyses for bulk RNA-seq, bulk ATAC-seq, single-cell RNA-seq, single-cell Multiome, and Spatial Transcriptomics/Visium HD datasets.
  • Process, quality control, analyze, visualize, and interpret high-dimensional sequencing and omics datasets.
  • Develop, optimize, maintain, and document reproducible computational pipelines and workflows to support scalable analysis across multiple research projects.
  • Partner closely with laboratory scientists and collaborators to translate biological questions into rigorous computational strategies and analytical plans.
  • Generate high-quality figures, summaries, and data outputs for internal research meetings, grant applications, manuscripts, and scientific presentations.
  • Manage computational analyses in a high-performance computing environment and ensure effective organization of data and analytical workflows.
  • Support ongoing and new research initiatives through timely, accurate, and scientifically rigorous analysis.
  • Contribute to manuscript preparation and other scholarly outputs arising from the laboratory’s research program.

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What This Job Offers

Job Type

Full-time

Career Level

Mid Level

Number of Employees

5,001-10,000 employees

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