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Post-Doctoral Research Fellow
Company Information
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.
A Post-Doctoral Research Fellow position is available in Dr. Wei Sun's group at Fred Hutchinson Cancer Center. The successful applicant will develop statistical/computational methods and software packages to study omics data. Specific topics/applications include, but not limited single cell multi-omics data, spatial transcriptomics, molecular images, and immunomics data such as T cell receptor (TCR) data, and deep learning methods for omics/imaging data. This could be a good position for someone with omics experience and would like to continue working in this area or someone with statistics background and limited omics experience but would like to learn more in this area.
The applicants should have a PhD or equivalent degree in Statistics, Biostatistics, Computer Science, Bioinformatics, or other related fields. The candidate should have solid training in statistical methods and excellent computational skills. In addition, background in biology and genetics, and organization and communication skills are plus.