Associate Scientist, Post Doc Fellow, Computational Immunology

MSD

Confirmed live yesterday High trust
Remote

Quick summary

Work type
Remote
Location
Cambridge, MA
Salary
$82,000–$92,000 / yr
Employment
Full-time
Posted
3 days ago
Freshness
Confirmed live yesterday
Closes
Oct 19, 2026

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $209k
This role $87k
$60k $285k
below market most similar roles pay here above market

This role pays less than 98% of similar roles. Most pay $171,399–$246,750 — the blue band above. At the midpoint, this role pays about $87k versus about $209k for comparable roles.

Based on 240 similar postings.

Employer

About MSD

MSD (Merck Sharp & Dohme) is the international name for Merck & Co., a major U.S.-based pharmaceutical company.

MSD currently has 11 open roles on FindRole.

Listed pay typically runs $82,000–$92,000 across 11 roles with salary data.

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At a glance

TL;DR · Associate Scientist, Post Doc Fellow, Computational Immunology

JOB TITLE: Associate Scientist, Post Doc Fellow- Computational Immunology The Postdoctoral Research Fellow joins a cross-functional translational research team to investigate cellular and tissue mechanisms in chronic immune-mediated inflammatory diseases, such as hidradenitis suppurativa. The fellow will analyze large-scale single-cell RNA-seq and spatial transcriptomics datasets from human tissue cohorts to identify disease-driving cellular programs, tissue microenvironments, and translational biomarkers. Key responsibilities include developing computational methods for data integration, annotation, and interpretation, as well as building cellular atlases and spatial niche discovery frameworks. The role requires proficiency in R, Python, GPU computing, HPC clusters, and AWS cloud environments. Candidates must apply advanced bioinformatics, statistical modeling, machine learning, and network biology to integrate transcriptomic, spatial, proteomic, and clinical data to generate mechanistic hypotheses and support therapeutic target evaluation and patient stratification.

What you'll do

  • Analyze large-scale single-cell RNA-seq, spatial transcriptomics, and multi-omics datasets.
  • Develop and implement computational methods for data integration, annotation, and interpretation.
  • Apply advanced bioinformatics, statistical modeling, machine learning, and network biology approaches.
  • Build comprehensive single-cell transcriptomic references and cellular atlases from diseased tissues.
  • Analyze spatial transcriptomics to localize disease-associated cell states and characterize multicellular interaction networks.
  • Identify biomarkers associated with disease biology, therapeutic response, and patient stratification.
  • Integrate multimodal datasets to construct disease-mechanism and translational biology models.
  • Lead publication-quality analyses and prepare manuscripts for peer-reviewed journals.

What we're looking for

  • Must currently hold a PhD or receive a PhD no later than spring 2027.
  • PhD must be in Computational Biology, Bioinformatics, Systems Biology, Genomics, Computer Science, Statistics, or a related discipline.
  • Must have strong programming skills in R and/or Python.
  • Must have experience analyzing large-scale genomics or multi-omics datasets.
  • Must have hands-on experience with GPU computing, HPC clusters, and AWS cloud environments for large-scale single-cell and spatial omics analyses.
  • Must be able to develop and optimize scalable computational pipelines for scRNA-seq, spatial transcriptomics, and multimodal biological data.
  • Must have a demonstrated publication record in computational biology, genomics, immunology, or related fields.
  • Experience with single-cell omics workflows, spatial transcriptomics platforms, or a background in immunology is preferred (preferred).

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