New 
Bioinformatics Analyst
 Spectraforce Technologies | |
 United States, Massachusetts, Cambridge | |
 Oct 03, 2025 | |
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Job Title: Bioinformatics Analyst III Duration: 2-3 months (through end of year) Location: Cambridge, MA / Hybrid Top 3 - 5 Skills Needed: 1. Implementing, training AI/ML models 2. Data pre-processing for AI compatibility 3. Domain knowledge of bioinformatics 4. Experience working with single cell and spatial data (transcriptomics, proteomics, epigenomics etc.) 5. Ability to communicate results clearly Job Description: The successful candidate will work closely with stakeholders across the IPSI (Immune Profiling & Systems Immunology in Immunology Discovery) organization to advance the Single-Cell Fibroblast Atlas initiative. The role will focus on applying AI/ML and advanced computational methods to large-scale single-cell transcriptomic, proteomics and spatial etc. datasets to define fibroblast states, map tissue-specific niches, and uncover their roles in health and disease. Key Responsibilities * Curate, harmonize, and analyze large-scale single-cell and spatial omics datasets (internal and public) with emphasis on fibroblast biology. * Develop and optimize predictive AI/ML models to classify fibroblast states, identify regulatory networks, and generate disease-relevant insights. * Integrate multi-modal data (scRNA-seq, spatial etc.) to construct a comprehensive fibroblast atlas. * Collaborate with other stakeholders. Impact By building the Fibroblast Atlas, the candidate will enable target discovery while driving cross-functional projects at the interface of data science, immunology, and translational medicine impacting the portfolio. Key Responsibilities * Support senior analysts and scientists in implementing, training, and troubleshooting AI/ML models tailored to single-cell and spatial omics data. * Ingest, clean, and preprocess large-scale single-cell transcriptomic and spatial datasets (public and internal) for single-cell atlas workflows. * Collaborate with immunology and computational teams to translate biological questions on fibroblast states, niches, and disease roles into computational solutions. * Document data curation, processing, and modeling pipelines to ensure reproducibility and transparency across the atlas project. * Assist in interpreting model outputs to generate insights into fibroblast heterogeneity, tissue-specific function. * Contribute to time-sensitive projects with critical deliverables, supporting target discovery and prioritization within the fibroblast atlas framework. Qualifications: * MS degree (5+ years of experience) or PhD (0+ years of experience) in a quantitative field (Bioinformatics, Computational Biology, Computer Science, Computational Genetics, Biostatistics, AI/Machine Learning, or related discipline). * Proficiency in Python and standard ML/data science libraries. * Experience working on HPC or cloud environments for large-scale omics and imaging datasets. * Domain knowledge in single-cell analysis, spatial omics, or systems immunology, ideally with exposure to fibroblast or stromal cell biology. * Strong attention to detail, documentation, and communication skills. * Ability to independently design, execute, and troubleshoot computational workflows. Preferred Technical Skills: * Experience with NumPy, Pandas, Scikit-learn, Matplotlib, and Seaborn. * Familiarity with deep learning frameworks (TensorFlow and/or PyTorch). * Proficiency with Git for version control and collaboration. * Hands-on experience with single-cell data analysis tools (e.g., Scanpy, Seurat, Bioconductor, or equivalent). * Exposure to multi-modal integration methods (e.g., CITE-seq, ATAC-seq, proteomics, imaging mass cytometry, spatial transcriptomics). Additional Technical Skills (a plus): * Experience with OpenCV, Scikit-image, or computer vision models for imaging datasets. * Knowledge of cell type annotation, clustering, and trajectory inference methods. * Experience building multi-modal AI/ML models that link transcriptomic, proteomic, and imaging data. | |