• Post-Doctoral Research Fellow

    Job ID
    Regular Full-Time
    Fred Hutchinson Cancer Research Center
    Biostatistics, Bioinformatics and Computational Biology
  • Overview

    Post-Doctoral Research Fellow/Research Associate - Postdoctoral position to develop efficient Bayesian phylogenetic inference methods


    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.


    There is a lot more sequence data than in the early 2000’s, but inferential algorithms for Bayesian phylogenetic inference haven’t changed much since that time. There have definitely been advances, such as more clever proposal distributions, swapping out heated chains, and GPU-enabled likelihood calculations, but the core remains the same: propose a new state via a small branch length and/or tree structure perturbation, and accept or reject according to the Metropolis choice. Furthermore, the community has packed more and more complexity into priors and models, which would lead to a computational bottleneck even with a fixed number of sequences. 


    It’s time to improve inferential algorithms. Part of our inspiration lies in watching the revolution that has occurred in computational statistics in the last decade, in which the menu has greatly expanded beyond MCMC to include sequential Monte Carlo (SMC), Hamiltonian Monte Carlo (HMC), and variational inference, to name a few. These algorithms are making qualitative improvements in the scale of data that can be incorporated into analysis, and come from new mathematical foundations with provable statistical properties. The other part of the inspiration, well, just comes from being annoyed that we have this fairly hard limit of 1,000 sequences for Bayesian phylogenetic inference. So, Vladimir Minin and I teamed up on a successful grant application to develop new inferential methods. 


    We thus have an open postdoc position to work on novel efficient Bayesian phylogenetic inference methods. We would like to find someone who can collaborate with us on methods development and implementation, thus both advanced knowledge of Bayesian statistics and programming expertise are needed. Experience with an existing code base for phylogenetics would be a big plus. 


    The position will come with a competitive postdoc-level salary with great benefits for one year, with possibility of extension. Fred Hutchinson Cancer Research Center, home of about 190 faculty including three Nobel laureates, is an independent, nonprofit research institution dedicated to the development and advancement of biomedical research. The environment is lively yet casual, with a strong emphasis on collaborative work. The Center is housed in a lovely campus next to Lake Union a short walk from downtown, and a slightly longer walk from the University of Washington. Powerful computing resources and a helpful IT staff await. 


    You can find out more about our group by visiting: 


    Minimum qualifications:

    • Ph.D. in biology, computer science, math, or another relevant area
    • Solid foundation in Bayesian phylogenetics or other challenging Bayesian estimation problem
    • Strong computer programming skills
    • Clear ability for independent research


    If you are interested in this position, please submit the following materials:

    • Two representative publications
    • Code samples
    • CV

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