Description

Fred Hutchinson Cancer Center is an independent, nonprofit organization providing adult cancer treatment and groundbreaking research focused on cancer and infectious diseases. Based in Seattle, Fred Hutch is the only National Cancer Institute-designated cancer center in Washington.

With a track record of global leadership in bone marrow transplantation, HIV/AIDS prevention, immunotherapy and COVID-19 vaccines, Fred Hutch has earned a reputation as one of the world’s leading cancer, infectious disease and biomedical research centers. Fred Hutch operates eight clinical care sites that provide medical oncology, infusion, radiation, proton therapy and related services, and network affiliations with hospitals in five states. Together, our fully integrated research and clinical care teams seek to discover new cures to the world’s deadliest diseases and make life beyond cancer a reality.

At Fred Hutch we value collaboration, compassion, determination, excellence, innovation, integrity and respect. Our mission is directly tied to the humanity, dignity and inherent value of each employee, patient, community member and supporter. Our commitment to learning across our differences and similarities make us stronger. We seek employees who bring different and innovative ways of seeing the world and solving problems.

The goal of its Public Health Sciences Division, which is home to the nation’s oldest program devoted to cancer prevention research, is to identify strategies that would ultimately reduce the incidence of and mortality from cancer and other diseases.

Responsibilities

The successful applicant will work closely with Dr. Yingqi Zhao, and other collaborators to develop statistical and machine learning methods for medical decision-making in cancer prevention and early detection. Key areas of focus include, but are not limited to, designing clinical decision rules for cancer early detection using real-world data such as Electronic Medical Records (EMRs), developing AI tools for integrating multimodal data in early detection, and developing EMR-based algorithms to identify high-risk populations. The applicant will have the opportunity to engage in research across a wide range of statistical areas and will gain access to data from various real-world studies. These efforts will result in both methodological and collaborative publications in high-quality, peer-reviewed journals.

Requirements

MINIMUM QUALIFICATIONS:

• Suitable applicants should complete (or nearly complete) a Ph.D. or equivalent in Statistics,Biostatistics, or a similar quantitative field prior to their appointment.
• The candidate should have solid training in statistical methods and computational skills.

PREFERRED QUALIFICATIONS:

• Experience with real-world data analysis, AI and machine learning, causal inference, and precision medicine are plus.

Please include the following materials in your application:

• CV;
• Two (2) publication samples or preprints;
• Contact information for three (3) references. 

The annual base salary range for this position is from $80,172 to $95,014, and pay offered will be based on experience and qualifications.

This position may be eligible for relocation assistance.  

This position is not eligible for H-1B sponsorship at this time.