Computational Genomics Research Scientist

We are seeking a Computational Genomics Research Scientist to support the development of transformative cell and gene therapies across Vertexs research portfolio. This Boston-based position is part of the global Data and Computational Sciences organization and will collaborate closely with research teams spanning stem cell biology immunology gene editing and pre-clinical development to design studies execute and analyze complex genomic analyses and ultimately generate biological insights that drive early research across multiple disease programs. As an embedded computational scientist you willbe responsible for performingbulk and single-cell sequencinganalyses spatial transcriptomics andmultiomicprofiling to help uncover the molecular programs that govern therapeutic cell identity differentiation function and safety to accelerate the development of next-generation cell and gene therapies.

This is a Boston based hybrid position requiring 3 days/week onsite.

Key Responsibilities

• Collaborate closely with cross-functional research teams to identify key scientific questions that can be addressed through genomics sequencing and bioinformatics approaches.
• Lead the application and advancement of spatial transcriptomics methods collaborating across teams and sites to develop implement and share analytical best practices.
• Analyze and integrate diverse genomic datasets including bulk RNA-seq single-cell profiling spatial transcriptomics and other multiomic datasets to generate actionable insights.
• Perform sophisticated computational analyses of sequencing and other biological data through deep critical thinking incorporation of published findings and best practices from the field strong statistical rigor and data science visualizations
• Distill complex analyses and scientific results into key take-home messages and recommendations for next steps to a broad audience.
• Partner with computational and software teams to improve analytical workflows reproducibility usability and robustness.
• Practice reproducible research and maintain well-documented version-controlled analytical workflows.
• Author study reports and technical documentation to support research and regulatory activities.
• Evaluate emerging genomics technologies and computational methods and incorporate new approaches where appropriate.

Knowledge and Skills:

• A proven track record in the analysis visualization and interpretation of genomic and next-generation sequencing (NGS) data
• Solid scientific understanding of gene editing the role of genetic variation in human disease molecular biology and cellular biology
• Expertise with applying computational methods and bioinformatics tools to large-scale data
• Solid understanding of statistics

Education and Experience:

• Ph.D. in computational biology bioinformatics genomics systems biology biomedical engineering statistics computer science or a related quantitative discipline with 0-3 years of relevant postdoctoral or industry experience; or a Masters degree in a related field with 3 years of relevant industry experience.
• Demonstrated expertise in the design analysis visualization and interpretation of single-cell genomics and spatial transcriptomics experiments
• Proficiency in Python and/or R for scientific computing and data analysis.
• Experience working in Linux-based high-performance computing (HPC) and/or cloud computing environments.
• Strong foundation in statistics experimental design and reproducible computational research.
• Proven ability to derive biological insight from complex datasets and translate findings into actionable recommendations for research teams.
• Excellent communication and presentation skills with the ability to effectively convey complex scientific findings to multidisciplinary audiences.
• Demonstrated ability to work collaboratively within cross-functional teams and contribute to a positive team-oriented environment.