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.
A highly motivated bioinformatician is sought to support research in the lab of Dr. Finak at Fred Hutchinson Cancer Research Center in Seattle, WA.
About the Lab
We are part of the RGLab, the Biostatistics, Bioinformatics, and Epidemiology program and the Vaccine and Infectious Disease Division of Fred Hutch in Seattle. We develop statistical methods and software tools for the analysis of high throughput biological data with an emphasis on immunology and vaccine research. We work with bench scientists and clinicians to understand and ultimately help develop vaccines and/or cure severe diseases such HIV, malaria, and cancer. We are a diverse group, with training in Statistics, Computer Science, Web Development, Bioengineering, Bioinformatics, and Computational Biology. Learn more about us at rglab.org and see some of our work on GitHub (github.com/RGLab).
Dr. Finak is seeking a bioinformatician / sofware engineer to help build the next generation of computational flow cytometry tools under the Flow Cytometry Data Standards, Integration and Analysis R01 award. The successful candidate will help develop, implement and optimize computational flow cytometry software tools and analytic pipelines for large, clinical and non-clinical flow and mass cytometry data sets. Leveraging R and C++, we are building open source tools to enable analysis, integration, and sharing of large flow cytometry data sets with a focus on facilitating reproducible research. The candidate will work as part of a team to support data analysis and software development and international collaborations. The candidate is expected to adhere to good software development practices (e.g. design, unit tests, documentation, code review), and participate in regular team meetings.
To be considered, candidates must have:
Please apply with your CV and a letter summarizing previous work experience.