The Position We are seeking a highly motivated Bioinformatics Scientist to join our Translational Genomics group supporting computational efforts across the Research organization. Our Translational Genomics efforts span the interface of human genetics, functional genomics, molecular biology, disease model engineering, and advanced computational methodology. This group works closely with our disease area scientists to identify new therapeutic hypotheses and advance transformative medicines. Working in a highly collaborative environment, the successful candidate will develop and apply bioinformatics resources to support next-generation sequencing applications in addition to methods aimed towards accelerating our advanced animal and cell engineering and genetic screening platforms. He/she is expected to play an active role in subsequent analysis and interpretation of data in close collaboration with wet lab scientists. Ultimately this work will deepen our understanding of biological systems and provide insight for the development of enhanced engineering workflows. towards accelerating our advanced animal and cell engineering and genetic screening platforms. He/she is expected to play an active role in subsequent analysis and interpretation of data in close collaboration with wet lab scientists. Ultimately this work will deepen our understanding of biological systems and provide insight for the development of enhanced engineering workflows. As a member of the Genentech Bioinformatics & Computational Biology department, he/she will work both independently and as a member of interdisciplinary teams, carry out data analysis and integration across various domains, and apply best-in-class algorithms — or develop new algorithms — that directly address motivating biological questions. Regular publication of both scientific and methodological results is strongly encouraged. Finally, the successful candidate will be able to effectively present complex results in a clear and concise manner that is accessible to a diverse audience of quantitative, experimental scientists. Requirements PhD in bioinformatics, computational biology or similar, with a strong publication record. Alternately, a PhD in molecular biology with a very strong record of high-throughput data analysis, supported by publication in this area. A solid understanding of algorithmic approaches to analyze genomic data as well as tools and genome databases. Candidates with working knowledge of genome editing and gene expression/function will be prioritized. Experience and interest in analyzing and interpreting data generated by next-generation sequencing technologies such as long read sequencing and a variety of single-cell sequencing applications. An understanding of the statistical principles, machine learning methods and current best practices in high-throughput molecular data analysis. Strong experience in the use of a high-level programming language such as R or Python for complex data analysis, familiar working in Linux and HPC compute environment. Exceptionally strong communication, data presentation and visualization skills. Ability to work both independently and collaboratively, and to handle several concurrent, fast-paced projects.
