Scientist/Senior Scientist, Computational Biology - Genomics

My client is seeking a motivatedComputational Genomics Scientistwith expertise in NGS data analysis and/or methods development to join their team in wither San Deigo, CA or Boston, MA. This client is focused on 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 their 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)

Minimum Qualifications

• 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

by Jobble