Personalis is a rapidly growing cancer genomics company transforming the development of next-generation therapies by providing more comprehensive molecular data about each patient’s cancer and immune response. Our ImmunoID NeXT Platform® is enabling the development of next generation immuno-oncology therapeutics and diagnostics.
You will work with a world-class, dynamic team of bioinformatics scientists, software engineers, and laboratory scientists, developing, testing, and applying cutting-edge cancer genomics biomarkers for immunotherapy response. You will perform statistical analyses on data generated in partnership with high-profile academic and industry collaborators, as well as on public datasets. Here, you will develop biological signatures using our exome-scale DNA, RNA and cfDNA platforms, and apply these novel biomarkers in exciting cancer patient cohorts. Your work will directly contribute to a new generation of genomics-based precision-medicine products in immuno-oncology and cancer clinical trials, diagnostics, and therapeutics being used by pharma, biotech, hospitals, and clinicians.
Create a statistical framework to develop novel, integrated immunotherapy biomarkers on our exome-wide DNA, RNA and cell-free platforms
Design and execute scientific collaborations with external academic groups focused on demonstrating the performance and clinical utility of identified biomarkers and internally developed tools
Work cross-functionally to translate findings into actively developed cutting-edge products
Publish results and present at conferences in exciting areas, including cell-free DNA, cancer genomics, and immuno-oncology
Advanced degree (PhD) in bioinformatics, genomics, computational biology, or a related field
Deep understanding of cancer genomics and immuno-oncology
Proficiency with at least one common programming language (e.g., Python, R)
Experience with applied statistics and machine learning
Experience processing and analyzing NGS data (DNA and RNA)
Demonstrated ability to identify novel biological insights from genomic datasets
Knowledge of neoantigens, immune checkpoint therapies, and tumor escape mechanisms
Knowledge of predictive biomarkers for cancer
Experience working with large cancer patient cohorts for biomarker development
Familiarity with cancer databases: Cosmic, TCGA, dbGAP, etc.
Experience with BASH scripting and Unix/Linux command line tools
Familiarity with grid computing systems such as SGE
Personalis is an Equal Opportunity Employer/Minorities/Females/Veterans/Disabilities. Personalis offers a competitive compensation package.