Computational Scientist 3, Immunology Job at Genentech in South San Francisco, CA
Position Description
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.
Recently, exciting developments at Genentech and elsewhere have demonstrated the potential of inferring cellular disease state trajectories for the identification of novel drug targets. Genentech seeks a talented and highly motivated Computational Scientist to play an integral role in data-driven projects in close collaboration with our Immunology Discovery Department.
The Opportunity
As an integral part of the team, you will focus on engaging in therapeutic discovery efforts and computational method development within our Autoimmune Disease Area Team, working closely with bench colleagues in the Immunology & Regenerative Medicine department. You will collaborate with an interdisciplinary team of research scientists to develop and employ computational approaches to understand the molecular mechanisms involved in diseases such as multiple sclerosis, systemic lupus erythematosus (SLE), systemic sclerosis (SSc, scleroderma), and type 1 diabetes.
You will have the ability to collaborate with a diverse group of scientists, work independently to achieve project goals, and contribute to scientific publications.
You will have access to pre-clinical and clinical samples and datasets.
You will have access to state-of-the-art technologies and pioneering research.
Who you are
You have a PhD in bioinformatics, biostatistics, computational biology, or a similar field. Postdoctoral experience is desirable but optional.
You have an intense curiosity about the biology of disease and an eagerness to develop new computational approaches and models to understand the molecular mechanisms underlying disease etiology.
You have demonstrated advanced skills in R and Python, performance optimization, version control systems, containerization, and continuous integration/delivery.
You have a deep understanding of computational techniques for analyzing high-throughput genomic, transcriptomic and/or proteomic datasets and an interest in applying novel approaches to explore and integrate such data at scale.
Preferred:
You have experience with high-throughput sequencing technologies (single-cell RNA-seq, spatial transcriptomics, ATAC-seq, immune repertoire sequencing, etc.).
You have relevant biological knowledge in immunology, with a background in autoimmune disease and/or lymphocyte/myeloid biology.
You have excellent communication and data presentation skills, including the ability to present complex scientific results to a diverse audience.
You have a relevant publication record of either scientific articles or software packages.
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Relocation benefits are available for this posting
The expected salary range for this position based on the primary location of California is $117,600 - 218,400. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law. A discretionary annual bonus may be available based on individual and Company performance. This position also qualifies for the benefits detailed at the link provided below.
All qualified candidates are encouraged to apply and will be considered. Our talent development strategy and processes have, however, pre-identified a potential candidate for this position.
Genentech is an equal opportunity employer, and we embrace the increasingly diverse world around us. Genentech prohibits unlawful discrimination based on race, color, religion, gender, sexual orientation, gender identity or expression, national origin or ancestry, age, disability, marital status and veteran status.
Roche is an Equal Opportunity Employer & prohibits unlawful discrimination based on race, color, religion, gender, sexual orientation, gender identity/expression, national origin/ancestry, age, disability, marital & veteran status.