Research Associate - Computational Immunology

The USC Mann School of Pharmacy and Pharmaceutical Sciences, Titus Department of Clinical Pharmacy, is seeking a Research Associate, Computational Immunology, to develop, implement, and apply advanced computational methods for immune-focused genomic and multi-omics analyses. This role will lead the design of scalable analysis pipelines, creation of robust software tools, and integrative interpretation of large, complex datasets (e.g., RNA-seq, TCR/BCR repertoire sequencing, single-cell multi-omics, proteomics, epigenomics). The successful candidate will partner closely with experimental and clinical teams to translate computational insights into actionable biological hypotheses and high-impact manuscripts and grant applications. Key Responsibilities Method and tool development Design, develop, test, and maintain computational tools for genomic and immunogenomic analyses (e.g., repertoire inference, clonotype tracking, antigen-receptor diversity metrics, cell-state modeling, and immune microenvironment profiling). Build and maintain reproducible, modular pipelines for high-throughput analyses using best practices in software engineering and scientific computing. Large-scale omics analysis Analyze and integrate large datasets across modalities (bulk RNA-seq, scRNA-seq, scATAC-seq, repertoire sequencing, proteomics/metabolomics), including quality control, normalization, batch correction, and statistical modeling. Perform differential analysis, pathway enrichment, deconvolution/cell composition inference, clonotype overlap and tracking, and longitudinal/paired analyses. Data integration, infrastructure, and databases Develop and manage analysis-ready databases and metadata frameworks; implement governance and documentation standards to ensure data integrity and reuse. Optimize computational workflows for high-performance computing (HPC) and/or cloud environments; implement scalable storage and compute strategies. Scientific collaboration and communication Collaborate with wet-lab and clinical investigators to define analysis plans, interpret results, and prioritize follow-up experiments. Prepare figures, reports, and reproducible notebooks; contribute to manuscripts, conference abstracts, and grant proposals. Present methods and results to multidisciplinary audiences; provide technical guidance and training to lab members as needed. Minimum Qualifications (One of the following) M.S. degree in Computational Biology, Bioinformatics, Genomics, Computer Science, Biostatistics, or a related discipline plus three years of relevant experience performing computational genomics/immunogenomics analyses and tool development; OR Ph.D. in Computational Genomics, Computational Immunology, Computational Biology, Bioinformatics, Biostatistics, Computer Science, or a closely related field. Required Technical Expertise Demonstrated experience developing genomic analysis tools and pipelines and analyzing large-scale omics datasets . Strong programming skills in Python and/or R ; proficiency with scientific computing libraries and data structures. Strong grounding in statistics for high-dimensional biology (e.g., regression models, multiple testing, experimental design, batch effects). Experience working in HPC/Linux environments , containerization (e.g., Docker/Singularity ), and job schedulers (e.g., SLURM or equivalent). Ability to write clear documentation and produce publishable-quality analyses and visualizations. Preferred Qualifications Immunogenomics experience including one or more of: TCR/BCR repertoire analysis, clonotype inference/annotation, diversity/selection metrics, and repertoire comparison across conditions. Single-cell immune profiling (e.g., scRNA-seq / CITE-seq / scATAC-seq) and multi-omic integration. Experience building and maintaining analysis databases and metadata schemas; familiarity with FAIR principles. Prior contributions to open-source software, internal toolkits, or published methods papers. Core Competencies Strong analytical reasoning and scientific rigor; ability to debug complex pipelines end-to-end. Excellent communication skills and ability to translate computational results for experimental and clinical collaborators. High ownership, organization, and attention to detail; ability to manage multiple concurrent projects and deadlines. Collaborative mindset with demonstrated ability to work in multidisciplinary teams. The annual base salary range for this position is $71,000 - $89,000. When extending an offer of employment, the University of Southern California considers factors such as (but not limited to) the scope and responsibilities of the position, the candidate's work experience, education/training, key skills, internal peer equity, federal, state, and local laws, contractual stipulations, grant funding, as well as external market and organizational considerations. Minimum Education: Ph.D. or equivalent doctorate Minimum Experience: 1 year Minimum Field of Expertise: Directly related education and experience in research specialization with advanced knowledge of equipment, procedures and analysis methods. #J-18808-Ljbffr University of Southern California