Scientist, Systems Immunology
About The Position
AbbVie Immunology is expanding its discovery Systems Immunology team in Cambridge, Massachusetts. The team identifies targets for autoimmune and chronic inflammatory diseases by computationally analyzing human disease tissue-derived datasets and validating targets with humanized experimental approaches. The Computational Immunology Scientist develops and implements computational approaches to understand disease biology and drug responses using high-throughput molecular profiling data. The role integrates single-cell RNA-seq, scATAC-seq, TCR/BCR repertoire, bulk RNA-seq, and Olink proteomics data to characterize disease-associated cell states, investigate gene regulatory networks, and identify therapeutic opportunities. Working with a multidisciplinary team, the scientist analyzes multiomics datasets to derive insights into immunological diseases and identify therapeutic targets relevant to patient cohorts and AbbVie pipeline drugs. The scientist also contributes to conference presentations, peer-reviewed publications, new drug applications, and regulatory filings. The position is based in Cambridge, Massachusetts, and involves collaboration with internal and external scientists.
Requirements
- BS or MS degree in computational biology, bioinformatics, genomics, biostatistics, computer science, or a related quantitative field.
- Typically 5–7+ years of relevant experience with a BS, or 2–5+ years with an MS.
- Hands-on scRNA-seq analysis experience, or experience with scATAC-seq or TCR/BCR analysis, and interest in developing expertise across both.
- Proficiency in Python and/or R.
- Experience working in Linux-based computing environments.
- Experience with commonly used bioinformatics tools and frameworks such as Scanpy, AnnData, Cell Ranger, scvi-tools, DESeq2, GSEA, WGCNA, or related methods.
- Working knowledge of statistical analysis, multiple-testing correction, batch effects, and biological replication in high-dimensional datasets.
- Ability to translate biological questions into analyses, interpret and communicate results critically, collaborate effectively, manage multiple priorities, and deliver high-quality work with attention to detail.
Nice To Haves
- Experience analyzing Olink or other high-plex proteomics datasets.
- Experience with CITE-seq, ATAC-seq, spatial transcriptomics, or integrative multi-omics analysis.
- Experience building or benchmarking machine-learning models, including convolutional neural networks, autoencoders, generative models, transfer learning, or foundation models.
- Experience with cloud or high-performance computing, including AWS and/or SLURM.
- Understanding of immunology and inflammatory disease biology.
- Experience supporting target discovery with experimental teams and communicating research through presentations, publications, or reports.
- Evidence of scientific communication through presentations, posters, publications, technical reports, or related research contributions.
Responsibilities
- Analyze scRNA-seq and CITE-seq datasets, including quality control, integration, clustering, and cell-type and cell-state annotation.
- Integrate patient cohorts with reference atlases and perform differential expression, abundance, and pathway analyses, accounting for donor variation and study design.
- Analyze scATAC-seq data to identify differential accessibility, transcription factor motifs, and candidate regulatory programs; integrate accessibility with gene expression to infer peak-to-gene relationships.
- Analyze TCR/BCR repertoires, including clonotype assignment, clonal expansion, diversity, V(D)J usage, and sharing across tissues or time points; link clonotypes to matched single-cell profiles.
- Analyze bulk RNA-seq and Olink proteomics data and integrate multiomics findings to support target prioritization and biomarker hypotheses.
- Maintain documented, version-controlled workflows and evaluate methods using cloud or high-performance computing.
- Collaborate with internal and external scientists to prioritize hypotheses for validation and communicate findings and limitations.
- Contribute to scientific presentations, peer-reviewed publications, new drug applications, and regulatory filings.
Benefits
- Paid time off, including vacation, holidays, and sick leave.
- Medical, dental, and vision insurance for eligible employees.
- 401(k) for eligible employees.
- Eligibility to participate in short-term incentive programs.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
