Cures Start Here. At Fred Hutchinson Cancer Research Center, home to three Nobel laureates, interdisciplinary teams of world-renowned scientists seek new and innovative ways to prevent, diagnose and treat cancer, HIV/AIDS and other life-threatening diseases. Fred Hutch’s pioneering work in bone marrow transplantation led to the development of immunotherapy, which harnesses the power of the immune system to treat cancer. An independent, nonprofit research institute based in Seattle, Fred Hutch houses the nation’s first cancer prevention research program, as well as the clinical coordinating center of the Women’s Health Initiative and the international headquarters of the HIV Vaccine Trials Network. Careers Start Here.
The Paulovich Lab at Fred Hutch is an interdisciplinary team whose mission is to develop and implement tools for protein quantification to enable precision medicine via patient selection and characterization of novel therapeutic targets. The lab has a major focus on mass spectrometry (MS)-based proteomics (both untargeted and multiple reaction monitoring), as well as integrating proteomic data with genomic and metabolomic data. Our group is highly collaborative, participating in national and international consortia in which teams of scientists, statisticians, and clinicians work together to solve clinical or biological problems to impact human health.
This is a terrific opportunity within the Paulovich lab for a data scientist to work closely with our interdisciplinary team of chemists, biologists, clinicians, and statisticians to leverage multi-omic datasets to understand and predict human cancer responses to therapies. We are looking for a highly motivated, interactive, Bioinformatics/ Computational Biologist to join our proteomics team to help drive translational projects forward towards clinical applications by performing analysis and interpretation of multidimensional “-omics” datasets (DNA, RNA, protein, metabolite, and clinical phenotype) from human tumors and preclinical models. The candidate will participate in the development of data pipelines, plan and conduct analyses, interpret results, design and implement data visualizations, and help prepare figures and text for funding proposals, reports, and publications. The ideal candidate should have the ability to work independently as one hub in an interdisciplinary team.