Open postdoc position to work on variational Bayesian phylogenetic inference

11 Dec 2018, by Erick

We are obsessed with finding efficient alternatives to random-walk MCMC for Bayesian phylogenetic inference. We have developed online sequential Monte Carlo theory and algorithms, phylogenetic Hamiltonian Monte Carlo, and inference via direct topology search and efficient marginal likelihood computation.

Come work with us on a strategy that is producing very promising results: variational Bayesian phylogenetic inference based on subsplit Bayesian networks. There are lots of opportunities for projects to flesh out this direction. We would like to find someone who can collaborate with us on methods development and implementation, thus knowledge of both Bayesian statistics and programming expertise are needed. Experience with an existing code base for phylogenetics would be a big plus.

We’re stoked but are happy to wait for the right person to fill the position. If you aren’t ready until this summer, no problem!

Apply here or just get in touch.

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