Bioinformatics Analyst II

ABOUT US

The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center (TLI) is Los Angeles County's preeminent independent, not-for-profit biomedical research hub, excelling in transforming scientific breakthroughs into practical therapies. With a $90 million annual budget, TLI is home to over 150 investigators and 500 staff, advancing 600 projects in areas such as Infection and Immunity, Cancer, and Women's Health. Founded in 1952, the Institute continues to train physician-scientists and manage healthcare programs for 60,000 underserved families throughout South Los Angeles.

SUMMARY

The Bioinformatics Analyst II supports clinical and translational research by processing, analyzing, interpreting, and presenting next-generation sequencing (NGS) and multi-omics data. This position assembles raw sequencing data into analysis-ready datasets, evaluates data quality, applies established and emerging bioinformatics methods, and prepares results for scientific publications and presentations. The role collaborates with laboratory members, investigators, and external partners and incorporates appropriate artificial intelligence approaches into analytical workflows.

DUTIES AND RESPONSIBILITIES

• Process and assemble raw NGS data into analysis-ready formats for genomic, transcriptomic, epigenomic, and other omics analyses.

• Perform quality control and evaluate the completeness, integrity, and analytical suitability of NGS datasets.

• Conduct reproducible bioinformatics analyses using R, Python, and other open-source bioinformatics and biostatistical tools.

• Access, curate, and analyze publicly available annotated genomic and omics databases to support research questions and comparative analyses.

• Develop, test, document, and refine analytical programs and workflows for clinical and translational research studies.

• Integrate, summarize, and visualize analytical results for manuscripts, abstracts, posters, presentations, and research reports.

• Assemble datasets, figures, tables, methods, and supporting documentation for scientific publications.

• Collaborate with laboratory members, investigators, statisticians, and external partners to define analytical needs, interpret results, and resolve data-quality or workflow issues.

• Evaluate and responsibly incorporate artificial intelligence and machine-learning methods into bioinformatics workflows when scientifically appropriate.

• Maintain organized code, metadata, analysis records, and version-controlled documentation to support reproducibility and data integrity.

• Remain current with advances in NGS, omics analytics, computational methods, and relevant public bioinformatics resources.

• Perform other duties as assigned in support of research program and institutional needs.

EDUCATION

• Master of Arts or Master of Science degree in Bioinformatics, Computational Biology, Biostatistics, Genomics, Computer Science, or a closely related quantitative discipline.

QUALIFICATIONS

• More than three years of relevant professional experience in bioinformatics, computational biology, genomics, or a related field.

• Demonstrated experience in NGS and omics analytics, including preparation of raw sequencing data for downstream analysis.

• Experience with transcriptomic, genomic, and/or epigenomic data analysis.

• Proficiency in R and working knowledge of Python and other open-source bioinformatics programs.

• Knowledge of public genomic and omics databases and methods for accessing, curating, and analyzing annotated datasets.

• Ability to assess NGS data quality, identify quality issues, and document appropriate corrective or analytical actions.

• Experience developing, adapting, or validating analytical workflows for clinical or translational studies.

• Ability to organize analytical outputs and contribute data, figures, tables, methods, and results to publications and presentations.

• Strong analytical, troubleshooting, documentation, collaboration, and scientific communication skills.

PREFFERED QUALIFICATIONS

• Experience supporting clinical, translational, cancer, or precision-medicine research.

• Experience with workflow tools, cloud or high-performance computing environments, and version control.

• Experience applying artificial intelligence or machine-learning approaches to biological or clinical datasets.

• Experience contributing analytical content to peer-reviewed publications or scientific presentations.

Please ensure your application is complete and signed; incomplete submissions will not be considered.

Background and Health Clearance Required

Equal Opportunity Employer/Affirmative Action/Drug-Free Workplace