Computational Genomics Scientist for Cell & Gene Therapies

Biopharma Careers; Boston (MA); Hybrid; USD 112,000 - 168,000; Full time

Job summary

Vertex seeks a Computational Genomics Research Scientist to advance cell and gene therapy research. The Boston-based role involves designing studies, executing analyses of bulk and single-cell sequencing, spatial transcriptomics, and multiomics to uncover molecular programs guiding therapeutic cell identity and safety.

As an embedded computational scientist, you will work with stem cell biology, immunology, gene editing, and pre-clinical teams, contributing to reproducible workflows and robust

Qualifications

• Experience analyzing genomic and NGS data (bulk and single-cell).
• Experience with spatial transcriptomics and multi-omics.
• Proficiency in Python and/or R for data analysis.
• Strong statistics and data visualization capabilities.

Responsibilities

• Collaborate with cross-functional teams to address genomic questions using sequencing and bioinformatics.
• Lead spatial transcriptomics method development and share best practices.
• Analyze bulk RNA-seq, single-cell data, and multi-omics to generate insights.
• Perform computational analyses with rigorous statistics and reproducible workflows.
• Convey results to diverse audiences and support regulatory documentation.

Skills

Genomics data analysis

Single-cell sequencing

Spatial transcriptomics

Large-scale data analysis

Python

R

Statistics

HPC/Cloud computing

Education

Ph.D. in computational biology or related field

0-3 years postdoc/industry experience or Master’s +3+ years

Tools

Python

R

Linux

HPC

Job description

Vertex seeks a Computational Genomics Research Scientist to advance cell and gene therapy research. The Boston-based role involves designing studies, executing analyses of bulk and single-cell sequencing, spatial transcriptomics, and multiomics to uncover molecular programs guiding therapeutic cell identity and safety.

As an embedded computational scientist, you will work with stem cell biology, immunology, gene editing, and pre-clinical teams, contributing to reproducible workflows and robust