Research Lab Technician II

The Department of Population and Public Health Sciences is seeking a Research Lab Technician II to support the computational workflows for our high-throughput molecular epidemiology and environmental health projects. The position focuses on the multi-omics integration and systems-level modeling of high-dimensional biological datasets. The core responsibility of this role is the integrative cross-platform analysis of genomic, epigenomic, and transcriptomic datasets. The successful candidate will deploy rigorous bioinformatics and statistical approaches to decipher how complex environmental exposures perturb the landscape of the human genome, epigenome, and transcriptome.

Key Responsibilities:

• Omics data pre-processing and analysis: Use scalable bioinformatics pipelines for pre-processing and analysis of raw omics data.
• Advanced Multi-Omics Data Integration: Execute workflows for linking genetic variation (e.g., SNPs, CNVs, eQTLs) to epigenetic modifications (e.g., DNA methylation, histone modifications) and transcriptomic alterations.
• High-Dimensional Statistical Modeling: Implement advanced multivariable linear and non-linear regression models to analyze cohort data while accounting for covariates and implementing strict False Discovery Rate control methods.
• Regression Diagnostics & Validation: Perform rigorous diagnostic validation on high-dimensional models to ensure model assumptions are met.
• Data Visualization: Transform large-scale omics outputs into publication-ready figures and tables for manuscripts and grant proposals.

Minimum Qualifications:

• Education: Bachelor's degree in bioinformatics, computational biology, biostatistics, computer science, or a closely related field.
• Experience: Minimum of 2 years of verified, dedicated experience handling medium/large-scale genomic, epigenomic, and/or transcriptomic data in an academic or industrial setting.

Technical Skills & Preferred Qualifications:

• Programming: Advanced proficiency in R and Bioconductor packages and/or Python. Comfortable navigating high-performance computing clusters (HPC/Slurm) and utilizing Unix/Linux command-line environments.
• Multi-Omics Subject Expertise: Demonstrable hands-on experience handling array / NGS-based epigenomic data (WGBS) alongside RNA-seq, miRNA-seq, or ATAC-seq, and WGS or WES, with deep intuition on how to systematically integrate these data.
• Statistical Rigor: Solid grounding in biostatistical methodology, including multivariable OLS regression, generalized linear models, dimensionality reduction techniques.
• Data Integrity & Stewardship: Rigorous code-documentation practices (Git/GitHub) and familiarity with open-source workflow management tools.

Hourly Range:

The hourly rate range for this position is $25.71 - $31.30. 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.