Ph.D. in Computational Language Evolution, ETH Zurich, Switzerland
project
Just as the biological species described by the phylogenetic tree evolve in complex ways, so does human language.
Over the past decade, phylogenetic and phylodynamic methods developed from the study of biological species and populations have become increasingly common in the field of linguistics.
This PhD program seeks to use and refine these methods to better understand the current mechanisms and historical dynamics of the emergence of linguistic diversity around the world.
The open position entails working closely with Prof. Dr. Tanja Stadler and other team members of the Computational Evolution Group to develop, implement, and apply novel inference methods in computational Bayesian systematics.
The overall goal is to develop the statistical and computational tools necessary to answer key questions in evolutionary linguistics surrounding the gains and losses of ancestral languages and how this process relates to human population dynamics and linguistic characteristics.
The initial goal of the project was to develop improved models for studying the relevant evolution of biological and linguistic features and the rate of diversification in linguistic phylogeny. The model currently in use is adapted from a macroevolutionary model of trait-dependent speciation.
Our goal is to further develop these features to allow for more continuous and discrete features, with a particular focus on horizontal transfer events that are critical in the locale.
This position will become the National Research Competence Center (NCCR) Evolutionary Language wwwevolvinglanguage.CH, a Swiss consortium with the ambitious goal of creating a new discipline – the science of evolutionary language, with the aim of the past and future of language.
The consortium is made up of leading scientists from traditionally separate academic fields, which allows us to gain diverse expertise from the humanities, social sciences, computational sciences, natural sciences, and medical fields for large-scale interdisciplinary collaborations.
Requirements:
We are looking for a highly motivated candidate with strong quantitative skills.
Before starting the position, you will complete a master's degree in applied mathematics, biostatistics, statistics, physics, or a related discipline.
Experience in linguistics, phylogeny, or systems dynamics is beneficial, but not a requirement for the position.
You'll be involved in interdisciplinary research as part of a team, so clear and effective communication skills are a priority.
We value an open and inclusive community culture.
As a member of the Computational Evolution group, you will help us maintain a positive team dynamics and a welcoming work environment.
The working language of our group is English, and it is not necessary to know German.
In line with our commitment to an open and inclusive group culture, we welcome applications from individuals of all demographic groups and personal backgrounds.
Job Description**