SCIENTIST (BIOINFORMATICS), MOLECULAR ONCOLOGY/ONCOLOGY BIOMARKER DEVELOPMENT
Organisation Name: GENENTECH
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Job Description:
The Position 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. The group’s primary focus is translation of complex molecular biomarker data, derived from clinical trial samples, 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. Requirements You have a PhD in bioinformatics, biostatistics, computational biology or similar, with a strong publication record. 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 for 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 have broad experience with data generated by one or more high-throughput molecular assays: next-generation sequencing, flow cytometry, etc. Experience with single-cell assays (e.g., single-cell RNA-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. What to expect from us A highly collaborative and dynamic research environment where we aim to translate our understanding of cancer biology and immunology to develop personalized therapies and diagnostics to transform clinical practice to benefit patient health. Access to clinical data sets and samples. Access to state-of-the-art technologies and pioneering research. Participation in seminar series featuring academic and industry scientists. Campus-like lifestyle with a healthy work-life balance. Mentored opportunities to further develop professional skills.
