PhD position in theoretical and computational modeling of gene regulatory networks and genome evolution

Your position

Our research group
Our research group is highly interdisciplinary, involving both an experimental section where researchers with a background in molecular biology and biophysics are experimentally studying genome evolution and gene regulation at the single cell level in bacteria, and a theoretical section where researchers with backgrounds in theoretical physics, computer science, and applied mathematics are using techniques from Bayesian probability, evolutionary theory, dynamical systems theory, and stochastic processes, to study the function and evolution of genome-wide regulatory networks in cells. We are particularly interested in uncovering the principles by which genome-wide regulatory networks specify and maintain cell identity in multi-cellular organisms, how cells control and exploit the noise in gene regulatory processes, and how gene regulation evolves. A full list of our group's publications can be found here .

This PhD position is not tied to a specific project and a research project will be designed in collaboration with the candidate, choosing from the current interests of our group. Current interests include the role of noise in gene regulatory strategies at the single cell level in bacteria (publication link , publication link , publication link ), the role of recombination in bacterial genome evolution (publication link ), the evolution of gene regulation in bacteria, and development of methods for inferring genome-wide gene regulatory networks in multi-cellular organisms, with the aim of attaining a quantitative understanding how they specify cell states and cell types (publication link , publication link ).

Your profile

For this position we are looking for candidates with strong mathematical and computational skills that are excited to work in the area of quantitative modeling of either gene regulatory networks at the single cell level or microbial genome evolution. Depending on the project, experience in areas such as next-generation sequencing data, stochastic processes, dynamical systems theory, population genetics, and Bayesian statistics will be desirable. Candidates do not necessarily have to have a biological background but should have a deep interest in the biological research questions and a strong desire to directly work with experimental data and (depending on the project) experimental collaborators. The candidates should have a good knowledge of English. German is helpful but not necessary. The salary is generous and is set according to the guidelines of the Swiss National Science Foundation. The start date will by mutual arrangement with the possibility to start immediately.