GRAIL is a healthcare company whose mission is to detect cancer early, when it can be cured. GRAIL is focused on alleviating the global burden of cancer by developing pioneering technology to detect and identify multiple deadly cancer types early. The company is using the power of next-generation sequencing, population-scale clinical studies, and state-of-the-art computer science and data science to enhance the scientific understanding of cancer biology, and to develop its multi-cancer early detection blood test. GRAIL is headquartered in Menlo Park, CA with locations in Washington, D.C., North Carolina, and the United Kingdom. GRAIL, LLC is a wholly-owned subsidiary of Illumina, Inc. (NASDAQ:ILMN). For more information, please visit www.grail.com.

This position is with the post-diagnosis team within GRAIL's Bioinformatics and Data Science organization. We are building a team to monitor the dynamics of disease burden and to characterize disease biology with a focus on the post-diagnostic setting. We work with interdisciplinary scientists, clinicians, engineers, and external collaborators to build new diagnostic products to support pharmaceutical development and cancer patient care.

You Will:

• Interact externally with pharmaceutical company collaboration partners to develop, improve, and/or test GRAIL algorithms for post-diagnostic product applications.
• Design, execute, and own analyses of large, sophisticated genomics datasets using machine learning and statistical methods to generate biological insights.
• Create and communicate meticulous scientific analyses.

Your Background Includes:

• Ph.D. in Bioinformatics, Statistics, Computational Biology, Cancer Biology, Genetics, Genomics, Biological Sciences, Computer Science, Physics, or equivalent preparation and experience.
• Robust understanding of modern statistical and machine learning tools for the analysis of genomics datasets and their use in clinical test development.
• Proven ability to apply these skills to uncover new biological insights from large genomics datasets.
• Expertise in R or Python is required, proficiency in Linux environment, version control tools, and reproducible research practices, experience with version control tools and reproducible research practices in a Linux environment.
• Proven track record of scientific contributions demonstrated by highly cited publications, tools, products, or data sets used in commercial products and by the scientific community, presentations at international conferences, intellectual property, and awards.
• 3-5+ years relevant experience in positions of increasing responsibility
• A history of delivering the design, execution and leadership of industry projects in a regulated environment, involving oncology applications, next-generation sequencing, or molecular tests.
• Self-direction, willingness to both teach others and learn new techniques.
• Effective written and verbal communication skills.

GRAIL is an Equal Employment Office and Affirmative Action Employer and does not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability or any other legally protected status. We will reasonably accommodate all individuals with disabilities so that they can participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

Following extensive monitoring, research, consideration of business implications, and advice from internal and external experts, GRAIL has made the decision to require all U.S. employees receive the COVID-19 vaccines as a condition of employment. “Full vaccination” is defined as two weeks after both doses of a two-dose vaccine or two weeks since a single-dose vaccine has been administered. Anyone unable to be vaccinated, either because of a sincerely held religious belief or a medical condition or disability that prevents them from being vaccinated, can request a reasonable accommodation.