Bioinformatician I- Immunology and Immunotherapy

The Bioinformatician I supports translational and clinical research within an Immune Monitoring Center by analyzing high-plex immunologic datasets generated across diverse diseases, tissues and patient cohorts. This role works closely with immunologists, clinicians, wet-laboratory scientists, and computational researchers to characterize immune-cell populations, cellular states, regulatory programs, and tissue-specific immune responses.

 

The position is responsible for the end-to-end processing and analysis of bulk, single-cell, multiomic, and spatial sequencing data, from raw-data processing and quality assessment through biological interpretation and communication of findings. A major focus of the role is translating complex sequencing data into biologically meaningful insights related to immune activation, inflammation, tissue microenvironments, disease mechanisms, treatment response, and potential biomarkers.

• Process, quality control, integrate, and interpret high-dimensional omics data to characterize immune-cell populations, transcriptional states, chromatin accessibility, inflammatory pathways, and disease-associated signatures.
• Characterize the composition and functional state of immune populations to study transcriptional states, immune activation, exhaustion, regulation, cellular heterogeneity, and identify disease-associated immune signatures, inflammatory pathways and candidate biomarkers across patient cohorts and experimental conditions.
• Integrate molecular, spatial, clinical, and experimental data across tissues, disease states, and treatment groups to investigate immune mechanisms and tissue microenvironments.
• Collaborate with wet-laboratory scientists, clinicians, immunologists, and pathologists on experimental design, assay troubleshooting, data interpretation, and translational research questions. 
• Develop and maintain reproducible analytical workflows and generate, reports, and summaries for ongoing projects, manuscripts, and other collaborative studies.

• B.S. in Biological Sciences, Bioinformatics, Computer Sciences, Statistics or related discipline; M.S. preferred
• 3 years experience required
• Working experience with genetics or statistics analysis software and online resources. Experience in programming environments such as Matlab, R statistical package, BioConductor, Perl or C++.

 

Preferred Skills

• Master’s degree in bioinformatics, computational biology, immunology, molecular biology, genetics, biostatistics, or a related field.
• Experience analyzing high-dimensional genomic datasets in a biological, clinical, or translational research setting.
• Strong understanding of molecular biology and immunology.
• Ability to interpret genomic results using immune-cell markers, signaling pathways, transcriptional programs, and disease-specific biological context.
• Strong Proficiency in R, python and related single-cell data structures, analytical frameworks and HPC.
• Knowledge of statistical methods used in genomic and high-dimensional biological data analysis.
• Familiarity with genomic databases, biological repositories, gene-set resources, and pathway databases.
• Strong scientific communication, organization, and collaborative problem-solving skills.