The Position

Our research group develops and applies methods to learn about evolution and immunology from molecular sequence data such as DNA and RNA. This is a rich source of fun and difficult problems in math/CS/(bio)-statistics, with real-world consequences.

The two questions that drive research in the group right now are:

• How can we turn phylogenetic (i.e. evolutionary tree) inference into a modern discipline of computational statistics?
• How can we use DNA sequencing to learn about the process by which we become immune to pathogens via exposure or immunization? (We can learn about the underlying biochemical mechanisms, host genetics, and immune exposures!)

We are looking for PhD students and postdocs interested in advancing these areas. We are a questions-driven rather than a methods-driven research group, so prospective students should come with an open mind to find and develop whatever methods are needed to advance understanding.

Nevertheless, to make things more concrete here are some things we’d like to do coming up:

• Probabilistic programming for multilevel models using Pyro
• Development a novel expectation-maximization algorithms for phylogenetics
• Development and characterization of phylogenetic variational approximations in PyTorch
• Developing succinct data structures for evolutionary histories and implementing them in modern C++
• Develop surrogate functions for phylogenetic likelihood computations under complex models
• Development of novel branching process priors

See our website for more information about what we do.

Environment

The environment in the Matsen group is lively yet casual, with a strong emphasis on collaborative work. The Center is housed in a lovely campus on Lake Union a short walk from downtown, and a slightly longer walk from the University of Washington. The Matsen group is in the newly-remodeled Steam Plant building overlooking the lake. Powerful computing resources and helpful IT staff await. Ideally you’d want to be on campus but long-term remote work is possible from these states: Alabama, Alaska, Arizona, California, Colorado, Hawaii, Idaho, Maryland, Minnesota, Montana, New York, Ohio, Oregon, South Carolina, and Texas.

We believe that science is for everyone. We have had researchers with a variety of backgrounds, including Latinx, Black, Asian, and Middle Eastern. We have had women, men, gay, and straight, and we welcome people of all sexual orientations and gender identities. We have had successful high schoolers, postdocs, people who were the first in their family to attend college, and one who had decided that college wasn’t for them. We have had researchers with backgrounds in biology, physics, statistics, math, and computer science.

We acknowledge the historical and present barriers for underrepresented groups, and work to increase diversity, equity and inclusion in computational biology. Members of underrepresented groups are especially encouraged to apply.

Please read our expectations of group members. By applying for this position, I expect that you will fulfill these expectations. I enthusiastically solicit feedback on these expectations or requests for clarification.

Qualifications

We are looking for PhD students and postdocs with a successful track record of independent research.

Essential skills

We have a diversity of research projects, each of which will require specific technical skills. However, we love to work with people who are:

• creative and thoughtful
• able to dive into the literature and find appropriate methods
• interested in developing their computer programming skills
• want to work together, often with biologists
• interested in the group’s research, and excited to contribute

Applying

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

• Two representative publications (if you are a PhD student you can substitute some other sort of project).
• A CV summarizing your education and work experience so far.
• The names and email addresses of two references.
• A code sample showing work that you are proud of. This has to be nontrivial, but doesn’t have to be long. Ideally it would be publicly accessible, e.g. on GitHub, but if that’s not possible an emailed attachment is fine too.

Please send these materials to: if you’re interested.