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  • Computational Biologist III(AI/ML)

    US Tech Solutions (Cambridge, MA)



    Apply Now

    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 f** rameworks **(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.**

    About US Tech Solutions:

    US Tech Solutions is a global staff augmentation firm providing a wide range of talent on-demand and total workforce solutions. To know more about US Tech Solutions, please visit www.ustechsolutions.com.

     

    US Tech Solutions is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.

     


    Apply Now



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