The Canary Foundation, Stanford University, and the Fred Hutchinson Cancer Research Center are jointly seeking a highly qualified post-doctoral fellow or research scientist with an interest in applying various modeling approaches to represent disease management strategies. The ideal candidate would have a Ph.D. or M.S. in a field related to quantitative modeling (decision modeling or game theory, biomathematics or biostatistics) or a substantive field that includes training in statistical modeling (health-outcomes research, economics, epidemiology, or computational biology). The ideal candidate should have experience in developing models related to a medical management problem including a detailed analysis of the literature. Experience in computer programming is essential. The ideal candidate will apply analysis expertise to extend and develop models of cancer natural history and cancer screening in order to answer important questions related to alternate screening strategies, cost-effectiveness, and other key parameters. Excellent verbal and written communication skills are key. This two-year position (possibly extendable to three years) will be funded by Canary Foundation, a non-profit organization focused on the early detection of cancer. Canary Foundation has assembled a team of scientists from several institutions (including Stanford University and the Fred Hutchison Cancer Research Center) to focus on in vitro diagnostics (e.g., blood biomarkers) and in vivo diagnostics (e.g., molecular imaging). As an integral part of this team, the position will receive mentorship from several participating investigators, including Drs. Sanjiv Gambhir, Nicole Urban, Sylvia Plevritis, and Patrick Brown. For further information or to apply for the position, please submit a cover letter and CV to hiring@canaryfoundation.org.

Canary Foundation is a non-profit organization dedicated to the goal of identifying cancer early through a simple blood test and then isolating it with imaging. Since 2004, Canary has raised over $27.9 million in pledges towards its goal of $100 million for early detection research. Its collaborative research programs span multiple disciplines and institutions. 100% of donations go to early detection research activities.