Bioinformatics Analyst III

Job Title: Computational Scientist (Bioinformatics / Computational Biology) Location: Cambridge, MA (Hybrid: 3 days onsite / 2 days remote) Pay: Overview The Immune Profiling & Systems Immunology (IPSI) team in Immunology Discovery is seeking a Computational Scientist to support high-impact bioinformatics work. The role focuses on applying computational and AI/ML methods to single-cell transcriptomic datasets to build an integrated single-cell atlas, enabling systematic evaluation of treatments that reverse disease-specific signatures. This role is best suited for a scientist who is comfortable with bioinformatics and computational biology (not pure machine learning), with the ability to analyze single-cell data and communicate findings effectively. Key Responsibilities • Build a Single-Cell Atlas by integrating existing single-cell datasets. • Analyze single-cell RNA-seq data to uncover disease- and treatment-associated networks and biomarkers. • Collaborate cross-functionally to apply computational approaches in therapeutic development. • Communicate findings clearly to both technical and non-technical stakeholders. Qualifications Education: • PhD or MS in Bioinformatics, Computational Biology, or a related quantitative field (fresh grads welcome) Skills: • Proficiency in Python programming. • Strong data analysis and visualization abilities. • Experience with single-cell RNA-seq data. • Familiarity with basic ML concepts. • Domain knowledge in bioinformatics. Preferred Skills • Must have: Scanpy (highly valued) • Pandas, Scikit-learn, Matplotlib, Seaborn. • Git/version control. • Experience with single-cell tools (Scanpy, Seurat, Bioconductor, etc.). • Exposure to multi-modal integration (CITE-seq, ATAC-seq, proteomics, imaging mass cytometry, spatial transcriptomics). • Familiarity with TensorFlow or PyTorch (preferred, not required). Additional Plus • Knowledge of cell type annotation, clustering, trajectory inference. • Experience building multi-modal AI/ML models linking transcriptomics, proteomics, and imaging data. Notes from Hiring Manager • Must be local to Cambridge due to hybrid requirement (3 onsite / 2 remote). • Start ASAP. • Skillset > Years of experience — manager values capability over tenure.