Fred Hutch is dedicated to the development and advancement of biomedical research to eliminate cancer and other potentially fatal diseases. As part of that goal, we offer the Mahan postdoctoral fellowship through our Computational Biology Program.
The fellowship provides a 21-month stipend to students while they pursue their research project in the laboratory of a Computational Biologist mentor.
To qualify, fellowship projects must focus on a topic of biological interest and have a computational or mathematical component. Laboratory trained scientists can satisfy the computational and mathematical requirement by including a training component in their proposal, while computationally strong candidates can include a laboratory training component. The research direction should reflect the interests and ideas of the applicant, although the final research proposal can be jointly designed.
Key application dates
Please check back Spring 2020 for the 2020/2021 application cycle
Please submit a:
Final Application Phase (if invited)
Upon invitation by the review committee, please submit a:
Project: Modeling the complex web of our polyclonal immunity
I study the n-body problem of our immune system. How does human serum, with its millions of different antibodies, protects us against pathogens? A lot of groups are examining how single antibodies fight flu or HIV, but few are investigating collective antibody action. As the field moves in this direction, it will shed light on the full repertoire our immune system unleashes against viral invaders.
Past Mahan fellows brought scientific and academic perspectives from around the world. They explored a variety of biological topics, from infectious disease to genetic expression. Students have gone on to pursue careers in laboratory science, which some staying on at Fred Hutch labs.
Project: Sequence data analysis in emerging infectious disease outbreaks
Sequence data from emerging infectious disease epidemics are becoming a universal tool for gaining insight into how pathogens spread and how to control them efficiently. The project focused on rapidly evolving RNA viruses and how their evolution can be used to understand their patterns of transmission. The West African Ebola virus epidemic of 2013-2016 was a primary focus of the project, where the factors affecting the virus' ability to spread and proliferate within the region were determined. Simultaneously, in collaboration with Nathan Grubaugh and Kristian Andersen at Scripps, as well as researchers from University of Oxford, the project also investigated the nature of a Zika virus outbreak in Florida in 2016. The final part of the project focusing on reconstructing the epidemiology of Middle East respiratory syndrome-associated coronavirus (MERS-CoV) at the interface between its two known major hosts, humans and camels, is currently in review.
Project: Understanding the disparate effects of DUX4 misexpression in muscular dystrophy and cancer
It is paradoxical how the misexpression of the same gene (DUX4) can cause disparate cellular phenotypes in two different diseases: muscle wasting in Facioscapulohumeral Muscular Dystrophy (FSHD), but uncontrolled cell proliferation in a subtype of B-cell precursor Acute Lymphoblastic Leukemia (BCP-ALL). By analyzing the RNA expression in patient samples from both these diseases, Guo-Liang aims to understand the molecular basis of DUX4-induced pathology in both diseases, as well as to use the insights gained from one disease to develop therapies for the other.
Project: Mapping host genetic barriers to zoonotic viral infection
My research focuses on how viruses such as influenza evolve to infect diverse host species. Zoonotic transmission of influenza from avian and swine hosts to humans have the potential to result in pandemics with severe public health consequences. I am working to map the evolutionary pathways by which influenza can adapt to new species, and using this map to assess adaptation and thus pandemic risk of novel influenza strains. Overall, these studies will help us understand the specifics of influenza adaptation, and more broadly, how viral evolution is shaped by host genetics.