Between the detailed knowledge of macromolecules provided by molecular and structural biology and the long-term chronicle of their history inferred from phylogenetic analysis, lies a gap in our understanding of the causal principles at work in the origin and evolution of macromolecular structure and function. Our work aims to narrow this gap, with a special emphasis on quantitative studies of mutational effects, and on the role of mutation in evolution.

This research utilizes computational and analytical modeling of evolution processes, as well as quantitative analyses of sequence and structure data from genes, proteins, and genomes. We welcome projects in any area of population genetics, molecular evolution or bioinformatics. Past work covers diverse topics from population-genetic modeling (Gitschlag, et al 2023) and empirical analysis (Stoltzfus and McCandlish, 2017) of the influence of mutational biases on adaptation, Bayesian methods for fossil calibration of trees, the evolution of ORFan genes in E. coli, and the evolution of the genetic code.

We especially welcome projects focused on testing (and developing implications of) the theory of arrival biases (see Wikipedia or Stoltzfus, 2019). 

key words

Bioinformatic; Computer simulation; Modeling; Molecular evolution; population genetics; theory

Citizenship:  Open to U.S. citizens

Level:  Open to Postdoctoral applicants