Overview In this role, you will apply computational genomics to support Vertex's cell and gene therapy programs. You will collaborate with cross-functional research teams to design and analyze genomic studies that uncover molecular programs guiding cell identity, differentiation, function, and safety. You'll advance spatial transcriptomics and multiomic approaches to drive early research across disease programs. You will translate complex results into actionable insights and contribute to reproducible, well-documented workflows.
Compensation / Benefits- annual bonus
- annual equity awards
- comprehensive medical/dental/vision benefits
- generous paid time off including company shutdowns
- educational assistance including student loan repayment
- 401(k) with matching
Responsibilities- Collaborate with cross-functional teams to address scientific questions using genomics, sequencing, and bioinformatics
- Lead development and sharing of spatial transcriptomics methods and best practices
- Analyze and integrate bulk RNA-seq, single-cell, spatial transcriptomics, and other multiomic data for actionable insights
- Perform sophisticated computational analyses with statistical rigor and effective data visualizations
- Distill results into clear take-home messages for diverse audiences
- Collaborate with computational and software teams to improve workflows, reproducibility, and robustness
- Maintain reproducible research with version-controlled workflows and well-documented analyses
- Author study reports and documentation to support research and regulatory activities
- Evaluate new genomics technologies and computational methods and adopt where appropriate
Key requirements- Proven track record in analysis, visualization, and interpretation of genomic and NGS data
- Solid understanding of gene editing, genetic variation in human disease, molecular and cellular biology
- Expertise in applying computational methods and bioinformatics tools to large-scale data
- Strong foundation in statistics
- Ph.D. in relevant field with 0-3 years postdoc/industry experience or Master's with 3+ years industry experience
- Expertise in design, analysis, visualization, and interpretation of single-cell genomics and spatial transcriptomics experiments
- Proficiency in Python and/or R for scientific computing
- Experience with Linux-based HPC and/or cloud computing environments
- Ability to translate complex findings into actionable recommendations
- Excellent communication and presentation skills
- Collaborative mindset and ability to work in cross-functional teams
- excellent communication
- cross-functional collaboration
- data storytelling
- Python
- R
- single-cell genomics
