Postdoctoral Fellow - Computational Biology / Research Oncology, Yao/de Sauvage Lab
Genentech
Summary
This hybrid computational and wet lab based postdoctoral position will investigate the interactions between oncogenic pathways and lineage factors, specifically how the underlying chromatin landscape in tissues affects the oncogenic properties of the same driver mutations in different tissues and cells of origin. Mechanisms derived from in vivo cancer models will be used to interpret patient responses to cancer therapeutics across various indications.
Job description
The Opportunity
This hybrid computational and wet lab based postdoctoral position will investigate the interactions between oncogenic pathways and lineage factors, specifically how the underlying chromatin landscape in tissues affects the oncogenic properties of the same driver mutations in different tissues and cells of origin. Mechanisms derived from in vivo cancer models will be used to interpret patient responses to cancer therapeutics across various indications.
- Utilize in vivo cancer models to understand changes in the chromatin after the acquisition of driver mutations and/or treatment with cancer therapeutics.
- Analyze single cell and bulk omics datasets to form hypotheses and derive biological insights.
- Learn best practices in data analysis and potentially software development.
- Collaborate effectively within an interdisciplinary team of quantitative, experimental, and clinical scientists.
- Present complex results clearly and concisely to diverse audiences.
Who You Are
- Ph.D. in Cancer Biology, Computational Biology or related field
- Experience with in vivo cancer models (e.g. GEMM, xenograft) and in vitro cancer assays.
- Experience with bulk and/or single-cell omics data analysis (e.g. bulk RNA-seq, ATAC-seq, ChIP-seq and single-cell RNA-seq/ATAC-seq)
- Proficiency in R or Python is required
- Demonstrated ability to drive at least one key research project, as evidenced by first-author publications in high-impact journals
- Strong communication skills and ability to work in a team environment.
Requirements
- Ph.D. in Cancer Biology, Computational Biology or related field
- Experience with in vivo cancer models (e.g. GEMM, xenograft) and in vitro cancer assays
- Experience with bulk and/or single-cell omics data analysis (e.g. bulk RNA-seq, ATAC-seq, ChIP-seq and single-cell RNA-seq/ATAC-seq)
- Proficiency in R or Python is required
- Demonstrated ability to drive at least one key research project, as evidenced by first-author publications in high-impact journals
- Strong communication skills and ability to work in a team environment
Benefits
- Relocation benefits
- Professional development workshops
- Networking opportunities
- Mentorship
- Competitive salary
Company overview
Genentech, founded in 1976 and now a member of the Roche Group, is widely recognized as the pioneer of the biotechnology industry. The company has been at the forefront of scientific innovation for nearly 50 years, using human genetic information to develop novel medicines for serious and life-threatening diseases. Genentech's transformational discoveries include the first targeted antibody for cancer and the first medicine for primary progressive multiple sclerosis. With over 10,000 employees, the company operates from its South San Francisco headquarters and maintains a strong focus on oncology, immunology, neuroscience, ophthalmology, and infectious diseases. Genentech continues to pursue groundbreaking science while maintaining its startup spirit within the Roche organization, consistently delivering on its promise to improve patients' lives through innovative biopharmaceutical solutions.