As a member of the CCR Collaborative Bioinformatics Resource (CCBR) core team at the National Cancer Institute (NCI), I work at the intersection of biomedical innovation and cutting-edge cancer research. My role within CCBR allows me to serve as a bridge between computational expertise and life-changing cancer discoveries, supporting researchers across the NIH. Every day, I focus on delivering expert-level computational support that accelerates cancer research through data-driven genomics and high-performance computing.
I work within an integrated team structure that spans core and embedded bioinformaticians across multiple CCR laboratories. This collaborative environment allows me to learn constantly while contributing my expertise to projects ranging from basic cancer biology to clinical applications. Working at the Frederick National Laboratory means I’m part of an institution that meets the nation’s most urgent biomedical research needs. The opportunity to work at the forefront of cancer genomics within one of the world’s premier cancer research institutions means that every day brings new challenges, new discoveries, and new opportunities to make a meaningful impact on human health.
Job responsibilities
🧬 Collaborative “Multi-omic” Analysis
I partner directly with principal investigators across NCI’s Center for Cancer Research (CCR), diving deep into complex high-throughput sequencing datasets. My expertise spans whole genome and exome seq, and transcriptomics where I help researchers uncover patterns in “multi-omics” data to facilitate data driven scientific discoveries. I also guide researchers through experimental design and data strategies for complex cancer biology studies.
⚙️ Pipeline Development & Innovation
One of my role is contributing to the standardization and reproducibility of bioinformatic analyses across CCR. Our team builds and maintain robust, reproducible analysis workflows that span genomics, transcriptomics, epigenomics, and proteomics. Working with advanced scripting languages, using frameworks like Nextflow and Snakemake, and high performance computing, I create tools that empower researchers to focus on discovery rather than technical barriers. My familiarity with databases like TCGA, Ensembl, NCBI, and cBioPortal enables me to quickly access and integrate diverse data sources to answer complex research questions.