US Tech Solutions
Bioinformatics Analyst III (Computational Scientist- Immunology Discovery)
US Tech Solutions, Cambridge, Massachusetts, us, 02140
Overview
This role is Bioinformatics Analyst III (Computational Scientist- Immunology Discovery) for IPSI (Immune Profiling & Systems Immunology in Immunology Discovery). The base pay range is $50.00/hr - $55.00/hr. Duration: 2 months (with possibility of extension). Description
We are looking for a motivated and talented individual to join IPSI as a Computational Scientist. The successful candidate will work closely with stakeholders to integrate internal single cell datasets from peripheral blood mononuclear cells treated with multiple experimental conditions into a combined atlas. The role will focus on applying AI/ML and advanced computational methods to integrate large-scale single-cell transcriptomic datasets to benchmark and prioritize treatments and assess which assets reverse disease-specific signatures. Responsibilities
Build a Single-Cell Atlas: Utilize already generated single-cell datasets to build a comprehensive single-cell atlas. Analyze Single-Cell Data: Assist in the analysis of single-cell RNA-seq data to identify disease and treatment-associated regulatory networks and biomarkers. Communicate Findings: Support the team in interpreting results and presenting scientific data to both internal and external stakeholders. Collaborate with Teams: Work with cross-functional teams to leverage computational methods in therapeutic development. Impact: Build the atlas to enable integration of single-cell experiments across different conditions, facilitating comparison of asset signatures and evaluation of cellular responses under various stimulations and treatments. Preferred Skills
Experience with Pandas, Scikit-learn, Matplotlib, Seaborn and Scanpy. 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). Knowledge of cell type annotation, clustering, and trajectory inference methods. Experience building multi-modal AI/ML models that link transcriptomic, proteomic, and imaging data. Required Skills
Proficiency in programming with Python. Solid understanding of data analysis and visualization techniques. Experience working with single cell RNA-seq data. Familiarity with basic machine learning concepts. Domain knowledge of Bioinformatics. Some experience in a relevant academic or industry setting is preferred. Familiarity with omics data types (e.g., RNA-seq) and basic machine learning concepts. Strong problem-solving skills and a desire to learn. Education and Experience
MS degree (5+ years of experience) or PhD in a quantitative field (Bioinformatics, Computational Biology, Computer Science, or related field). 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. For more information, visit www.ustechsolutions.com. EEO Statement: 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. Recruiter Details
Name: Shivangi Shivpuri Email: shivangi.s@ustechsolutionsinc.com Internal Id: 25-49581
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This role is Bioinformatics Analyst III (Computational Scientist- Immunology Discovery) for IPSI (Immune Profiling & Systems Immunology in Immunology Discovery). The base pay range is $50.00/hr - $55.00/hr. Duration: 2 months (with possibility of extension). Description
We are looking for a motivated and talented individual to join IPSI as a Computational Scientist. The successful candidate will work closely with stakeholders to integrate internal single cell datasets from peripheral blood mononuclear cells treated with multiple experimental conditions into a combined atlas. The role will focus on applying AI/ML and advanced computational methods to integrate large-scale single-cell transcriptomic datasets to benchmark and prioritize treatments and assess which assets reverse disease-specific signatures. Responsibilities
Build a Single-Cell Atlas: Utilize already generated single-cell datasets to build a comprehensive single-cell atlas. Analyze Single-Cell Data: Assist in the analysis of single-cell RNA-seq data to identify disease and treatment-associated regulatory networks and biomarkers. Communicate Findings: Support the team in interpreting results and presenting scientific data to both internal and external stakeholders. Collaborate with Teams: Work with cross-functional teams to leverage computational methods in therapeutic development. Impact: Build the atlas to enable integration of single-cell experiments across different conditions, facilitating comparison of asset signatures and evaluation of cellular responses under various stimulations and treatments. Preferred Skills
Experience with Pandas, Scikit-learn, Matplotlib, Seaborn and Scanpy. 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). Knowledge of cell type annotation, clustering, and trajectory inference methods. Experience building multi-modal AI/ML models that link transcriptomic, proteomic, and imaging data. Required Skills
Proficiency in programming with Python. Solid understanding of data analysis and visualization techniques. Experience working with single cell RNA-seq data. Familiarity with basic machine learning concepts. Domain knowledge of Bioinformatics. Some experience in a relevant academic or industry setting is preferred. Familiarity with omics data types (e.g., RNA-seq) and basic machine learning concepts. Strong problem-solving skills and a desire to learn. Education and Experience
MS degree (5+ years of experience) or PhD in a quantitative field (Bioinformatics, Computational Biology, Computer Science, or related field). 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. For more information, visit www.ustechsolutions.com. EEO Statement: 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. Recruiter Details
Name: Shivangi Shivpuri Email: shivangi.s@ustechsolutionsinc.com Internal Id: 25-49581
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