Job Opportunity: Bioinformatics Scientist, Genentech, South San Francisco, CA
Genentech seeks a talented and highly motivated Bioinformatics Scientist to pursue reverse translational research projects in collaboration with our Molecular Oncology and Oncology Biomarker Development Departments.
Recently, exciting developments at Genentech and elsewhere have uncovered new avenues for interrupting the aberrant cell cycle pathways driving solid tumors. Our extensive high-dimensional molecular characterization of samples from clinical trials provide an outstanding opportunity for rapidly taking clinical insights back into the laboratory.
The primary focus of this position is on deep exploration of high dimensional clinical trial datasets, with the goal of translating findings into actionable biological insights that can guide our understanding of drug activity in patient tumors, characterize mechanisms of primary and acquired drug resistance, and identify subsets of patients who may benefit from specific therapeutic interventions.
A successful candidate will work with interdisciplinary teams, carry out data analysis and integration across various domains (High-throughput Transcriptomic, Genomic, Proteomic, Epigenomic data), and apply best-in-class algorithms — or develop new algorithms — that directly address the motivating biological and clinical 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, and clinical scientists.
Successful candidates will meet many of the following requirements:
- You have a PhD in bioinformatics, biostatistics, computational biology or similar. Alternatively, you have a PhD in molecular biology, immunology, etc. combined with a very strong record of high-throughput data analysis, supported by publication in this area.
- You are passionate about the relevant concepts in cancer biology and genetics. You are enthusiastic about learning more.
- You have postdoctoral experience in basic or translational research either in an academic or industry setting with a record of publication in lead positions.
- You might have experience with some of these types of high throughput molecular assays: next-generation sequencing (WES, RNAseq, ATACseq), flow cytometry, etc. Experience with single-cell assays (e.g., single-cell RNA-seq, Multiome-seq, or CyTOF) is a significant plus.
- You are comfortable with the statistical principles behind current best practices in clinical and high-throughput molecular data analysis.
- You have strong experience in the use of a high-level programming language such as R or Python for complex data analysis.
- You have exceptionally strong communication, data presentation and visualization skills.
- You are comfortable working both independently and collaboratively, and with handling several concurrent, fast-paced projects.