Senior Scientist, Computational Biology

Genentech•South San Francisco, CA

36d•Onsite

About The Position

A healthier future. It's what drives us to innovate. To continuously advance science and ensure everyone has access to the healthcare they need today and for generations to come. Creating a world where we all have more time with the people we love. That's what makes us Roche. Advances in AI, data, and computational sciences are transforming drug discovery and development. Roche's Research and Early Development organisations at Genentech (gRED) and Pharma (pRED) have demonstrated how these technologies accelerate R&D, leveraging data and novel computational models to drive impact. Seamless data sharing and access to models across gRED and pRED are essential to maximising these opportunities. The new Computational Sciences Center of Excellence (CoE) is a strategic, unified group whose goal is to harness this transformative power of data and Artificial Intelligence (AI) to assist our scientists in both pRED and gRED to deliver more innovative and transformative medicines for patients worldwide. The department of Research Oncology in Computational Biology and Medicine at Genentech seeks a talented and highly motivated senior scientist to deliver collaborative, data-driven research projects within our Research Oncology Department and drug development teams. The mission of the Research Oncology in Computational Biology and Medicine is to collaborate with other functions in gRED to develop new drugs to treat cancer patients. By combining computational analyses with pre-clinical and clinical data, we identify new targets, design strategies to improve drug efficacy, and address resistance mechanisms. The data-driven collaborative environment and science-focused approach offers unique opportunities to drive drug development and impact patient care. Applicants should be experts in computational biology with strong experience in integrating data from multiple modalities (high-throughput transcriptomic, epigenomic, and drug-response data) using systems biology, machine learning, or statistical methods as reflected by scientific publications. They should be able to work independently to achieve defined goals as well as investigate research questions from experimental and translational groups. Strong communication skills are required along with ability to work in a collaborative environment comprising computational and experimental biologists as well as machine learning scientists. Furthermore, they should have the scientific rigor and organizational skills to support multiple fast-paced projects in parallel. The successful candidate will be working directly with experimental group leaders in Research Oncology to analyze data and extract meaningful biological insights. The Senior Scientist will have opportunities to present their work internally and externally as well as contribute to scientific publications. In addition, they will have opportunities to develop as scientists under the mentorship of the department director and learn about drug development.

Requirements

You have a Ph.D. in Computational Biology, Systems Biology, or Bioinformatics with evidence of independent work such as postdoc experience.
You have strong experience in analyzing data generated by high-throughput molecular assays, especially single-cell NGS assays (e.g., scRNA-seq, scATAC-seq).
You are fluent in using high-level programming languages, such as R and Python, for analyzing complex biological data and skilled at data visualization.
You have experience in cancer biology and oncogenic signaling pathways, and have enthusiasm for learning more about specific diseases.
You understand and can explain the basic principles behind recent machine learning methods.
You have strong communication and data presentation skills.
You have strong organizational skills and feel comfortable working on multiple projects in parallel.

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