Scientist, Systems Immunology

What you'll do

• Perform quality control, integration, clustering, and cell-type annotation for scRNA-seq and CITE-seq datasets.
• Integrate patient cohorts with reference atlases to perform differential expression and pathway analyses.
• Analyze scATAC-seq data to identify differential accessibility, transcription factor motifs, and regulatory programs.
• Analyze TCR/BCR repertoires to assess clonotype assignment, diversity, and link them to single-cell profiles.
• Integrate bulk RNA-seq and Olink proteomics data to support target prioritization and biomarker hypotheses.
• Maintain documented, version-controlled workflows using cloud or high-performance computing environments.
• Contribute to scientific conference presentations, peer-reviewed publications, and regulatory filings.

What we're looking for

• BS or MS degree in computational biology, bioinformatics, genomics, biostatistics, computer science, or a related quantitative field.
• 5-7+ years of relevant experience for BS holders or 2-5+ years for MS holders.
• Hands-on experience in scRNA-seq analysis or experience with scATAC-seq or TCR/BCR analysis.
• Proficiency in Python and/or R and experience working in Linux-based computing environments.
• Experience with bioinformatics tools such as Scanpy, AnnData, Cell Ranger, scvi-tools, DESeq2, GSEA, or WGCNA.
• Working knowledge of statistical analysis, multiple-testing correction, batch effects, and biological replication in high-dimensional datasets.
• Experience analyzing Olink or other high-plex proteomics datasets (preferred).
• Experience with CITE-seq, ATAC-seq, spatial transcriptomics, or integrative multi-omics analysis (preferred).