Genomic Scientist - Genomic Analysis

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 Scientist, you will lead integrative bioinformatic analyses of RNA sequencing, methylation, long-read sequencing, and whole genome/exome sequencing (WGS/WES) data. You will be a key contributor to initiatives that integrate genomics into clinical care and advance research for pediatric rare diseases. This role involves developing bioinformatics pipelines, applying variant interpretation algorithms, managing collaborative projects, and translating complex clinical requirements from physician-scientists into actionable computational solutions.

• Hypothesis-Driven Data Analysis
  :
  Perform rigorous exploratory and inferential data analysis on high-dimensional genomic datasets using statistics, machine learning, and quantitative modeling to test biological hypotheses.
• Biological Discovery
  :
  Critically evaluate, contextualize, and extract actionable insight from disparate multi-omics sources to advance translational care and fundamental genomic research across Boston Children's Hospital.
• Pipeline Development & Maintenance
  :
  Build, adapt, and execute reproducible bioinformatics pipelines and variant interpretation workflows tailored to research and translational initiatives.
• Analytical Project Execution
  :
  Lead the computational execution of collaborative research studies; manage project milestones, resolve analytical bottlenecks, and deliver validated results under general supervision.
• Scientific Communication
  :
  Contribute significantly to peer-reviewed scientific manuscripts, present analytical findings at internal and external research forums, and document computational workflows for institutional knowledge-sharing.

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

• A minimum of one year of position-specific experience might potentially include experience acquired through MSc or Ph.D. studies.
• Solid analytical and scientific reasoning skills, evidenced by contributions to peer-reviewed scientific publications and technical presentations.
• Direct experience with human genetics research and human genomic datasets.
• Computational experience analyzing multi-omic datasets, specifically whole-genome/exome sequencing (WGS/WES), RNA sequencing, methylation, or long-read platforms.
• Familiarity with clinical NGS testing frameworks, variant annotation tools, and ACMG interpretation guidelines in a research setting.
• Proficiency in Python, R, and Bash within Linux/Unix High-Performance Computing (HPC) environments.
• Demonstrated ability to manage analytical tasks independently under general guidance, troubleshoot technical challenges, and collaborate effectively with multidisciplinary research teams.