Post-Doctoral Research Fellow (Temporary)
Fred Hutchinson Cancer Center (Fred Hutch) | |||||||||
paid holidays, sick time | |||||||||
United States, Washington, Seattle | |||||||||
1100 Fairview Avenue North (Show on map) | |||||||||
Nov 23, 2024 | |||||||||
Post-Doctoral Research Fellow (Temporary)
Overview 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. These values are grounded in and expressed through the principles of diversity, equity and inclusion. 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. Fred Hutch is in pursuit of becoming an anti-racist organization. We are committed to ensuring that all candidates hired share our commitment to diversity, anti-racism and inclusion. Responsibilities The Post-Doctoral Research Fellow will primarily work with Drs. Yingqi Zhao and Yingye Zheng on developing statistical and machine learning methods for study designs and decision-making in disease early detection. Specific topics include, but are not limited to, the design and analysis of randomized screening trials, benefit-harm analysis of cancer early detection tests, and development of clinical decision rules in cancer early detection and active surveillance. The applicant will have opportunities to pursue research in broad statistical areas and have access to data from various studies. These research works will lead to both methodological and collaborative publications in high-quality, peer-reviewed journals. Qualifications MINIMUM QUALIFICATIONS:
Ph.D. or equivalent in Statistics, Biostatistics, or a similar quantitative field.
PREFERRED QUALIFICATIONS:
A statement describing your commitment and contributions toward greater diversity, equity, inclusion, and antiracism in your career or that will be made through your work at Fred Hutch is requested of all finalists. The annual base salary range for this position is from $77,976 to $150,000 and pay offered will be based on experience and qualifications. Our Commitment to Diversity We are proud to be an Equal Employment Opportunity (EEO) and Vietnam Era Veterans Readjustment Assistance Act (VEVRAA) Employer. We are committed to cultivating a workplace in which diverse perspectives and experiences are welcomed and respected. We do not discriminate on the basis of race, color, religion, creed, ancestry, national origin, sex, age, disability (physical or mental), marital or veteran status, genetic information, sexual orientation, gender identity, political ideology, or membership in any other legally protected class. We are an Affirmative Action employer. We encourage individuals with diverse backgrounds to apply and desire priority referrals of protected veterans. If due to a disability you need assistance/and or a reasonable accommodation during the application or recruiting process, please send a request to Human Resources at hrops@fredhutch.org or by calling 206-667-4700. |