We are seeking a motivated Computational Genomics Scientist with expertise in NGS data analysis and/or methods development to join Vertex’s research site in San Diego, CA. A unique feature of Vertex is our focus on understanding the underlying disease biology in relevant primary human tissues and our reliance on developing screening assays using cell cultures developed directly from these tissues. Much of our genomic work supports characterizing disease phenotypes in primary tissue, elucidating the underlying genetic mechanisms of disease, and assessing our cultures and screening assays to ensure they represent in vivo conditions with high fidelity. To these ends, experience in one or more of the following areas is highly desired (ordered by priority):
• single-cell characterization (sc/snRNA-Seq)
• gene expression analysis (RNA-Seq, eQTL, Pathway/network analysis)
• bioinformatics engineering (programming, analytical pipeline development, data visualization, high-performance/cloud computing)
• statistical genetics (GWAS/PheWAS/Fine mapping/Gene burden testing)
• statistics and machine learning (traditional statistical analysis, decision theory, clustering, network analysis, text mining)
• evolutionary/population genetic sequence analysis (Population structure, Homology/Conservation inference)
This position is part of a growing global Data and Computational Sciences team focused on using advanced analytics to deliver transformative medicines to our patients by accelerating all areas of the drug discovery lifecycle. Your key tasks will be to collaborate with cross-functional project teams to design studies, analyze and interpret large-scale genomics data, and communicate results that will have critical impact on the development of cutting-edge, transformative therapies. You will play a key role in bringing together the needs of project teams with state-of-the-art computational biology tools, which will require proactive communication and seamless collaboration with both computational and experimental team members.
Key responsibilities:
• Collaborate with project teams, acting as the computational biology expert, to identify key needs and questions that can be addressed using genomics, sequencing, statistics, and/or bioinformatics
• Plan studies leveraging genetic and genomic data to answer critical biological questions and accelerate the development of transformational therapies
• Execute and iterate on analysis of large-scale sequencing data, in partnership with computational and experimental team members
• Visualize, summarize, and communicate findings to project teams and other key stakeholders
• Follow relevant cutting-edge advancements in the fast-paced field of genomics, bringing developments in-house or building upon them as appropriate
• Partner with team members to improve or expand computational methods and develop best-practice, easy-to-use analytical workflows to answer common genomics questions
• PhD or MS with experience in computational biology, statistical genetics, population genetics, bioinformatics, biomedical engineering, statistics, computer science, machine learning or a related field
• A proven track record in the analysis, visualization, and interpretation of genomic data types including next-generation sequencing (NGS) data
• Demonstrated ability to work closely with project teams and/or experimental collaborators to design studies and develop analyses to answer scientific questions
• Familiarity with applying computational methods and bioinformatics tools to large- scale data including proficiency with Linux/Unix systems and high-performance computing environments
• Experience with relevant analytical approaches and underlying statistical assumptions
• Detail-oriented and self-motivated approach to problem solving with excellent analytical rigor
• A team-oriented growth mindset that welcomes feedback from others and supports other team members; strong collaboration skills to work across teams and functions
• A positive attitude that enthusiastically tackles and overcomes challenges
• Strong organizational and time-management skills to prioritize needs and get things done
• Excellent presentation and communication skills, including the ability to tailor scientific content to audiences with different backgrounds