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 salar