Position Summary
Research Informatics supports basic, translational, and clinical pediatric research by delivering cutting-edge digital tools, high-performance computing (HPC), and advanced data science expertise. We bring together PhD-level bioinformaticians, genomic scientists, software engineers, and HPC specialists to collaborate with physician-scientists on work ranging from CryoEM to translational genomics.

As a Genomic Data Scientist, you will drive pipeline engineering and high-dimensional multi-omics analysis across pediatric rare disease initiatives. Working under general scientific direction, you will serve as a key technical and analytical contributor to genomics projects, architecting automated, reproducible workflow systems (e.g., Nextflow, WDL, Snakemake) to process and interpret RNA-seq, methylation, long-read, and whole genome/exome (WGS/WES) data.

Key Responsibilities

• Pipeline Engineering & Workflow Automation: Design, build, optimize, and maintain scalable, reproducible bioinformatics pipelines and automated variant interpretation workflows for research and clinical-grade multi-omics data.
• Hypothesis-Driven Data Analysis: Deploy automated analytical workflows to execute rigorous exploratory and inferential data processing on high-dimensional genomic datasets using advanced statistics, machine learning, and quantitative modeling.
• HPC & Infrastructure Optimization: Containerize computational tools (Docker/Singularity), implement version control (Git), and optimize code performance for efficient execution across High-Performance Computing (HPC) clusters.
• Biological Discovery & Project Execution: Partner with physician-scientists to translate raw multi-omics data into biological insights, managing computational project milestones and troubleshooting pipeline bottlenecks with minimal supervision.
• Documentation & Scientific Communication: Thoroughly document computational pipelines and code bases, contribute to peer-reviewed scientific publications, and present analytical methods at internal and external research forums.

Minimum Qualifications
Education:

• Bachelor’s degree; PhD in Genetics, Genomics, Computational Biology, Bioinformatics, or a related quantitative field highly preferred.

Experience:

• A minimum of one year of position-specific experience might potentially include experience acquired through MSc or Ph.D. studies.
• Demonstrated experience building, maintaining, and automating bioinformatics pipelines using workflow orchestration engines (e.g., Nextflow, WDL, Snakemake).
• Strong programming proficiency in Python, R, and Bash in Linux/Unix High-Performance Computing (HPC) environments, including experience with containerization (Docker/Singularity) and version control (Git).
• Computational experience analyzing multi-omic datasets (WGS/WES, RNA sequencing, methylation, or long-read platforms).
• Experience with human genetics research, variant annotation tools, and familiarity with clinical NGS testing frameworks or ACMG interpretation guidelines in a research setting.
• Demonstrated ability to manage pipeline development tasks independently under general guidance, troubleshoot technical software issues, and collaborate effectively with multidisciplinary research teams.