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Urgent! Bioinformatics Analyst III Job Opening In Cambridge Massachusetts – Now Hiring Katalyst Healthcares & Life Sciences

Bioinformatics Analyst III



Job description

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.

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.


  • 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.


  • 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.



Requirements:


  • 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.



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).


  • 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.



Top Skills:


  • Implementing, training AI/ML models.


  • Data pre-processing for AI compatibility.


  • Domain knowledge of bioinformatics.


  • Experience working with single cell and spatial data (transcriptomics, proteomics, epigenomics etc.).


  • Ability to communicate results clearly.





Required Skill Profession

Other General



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