PhD student in Computer Science or Bioinformatics

Project Background.
We are seeking a motivated PhD student to join our research team in developing advanced methods for phylogenetic network analysis, with a specific focus on network consensus algorithms. Significant progress has been made in consensus tree methodologies. A consensus tree is a phylogenetic tree that synthesizes multiple phylogenetic trees, each with the same leaf labels but possibly differing topologies. These trees are often generated through bootstrapping or other sampling techniques. Traditional approaches to consensus tree construction focus primarily on topological aspects, often overlooking the importance of branch length, which captures the temporal progression of genetic mutations. However, in the context of consensus networks, very few studies have introduced relevant concepts.

Project Objective.
Our project addresses this limitation by integrating branch-length data not only into the construction of consensus trees but also into network consensus construction. This more comprehensive approach aims to provide a richer and more accurate representation of evolutionary relationships by combining topological structure, branch frequency, clade frequency, and branch length.

The candidate must hold a Master’s degree in Mathematics, Computer Science, or Bioinformatics with a strong overall GPA.
Compensation: non-taxable scholarship of +20,000 CAD per year.

To apply, please send your CV, list of peer-reviewed articles (optional), and a cover letter to: Prof. Nadia Tahiri

PhD student in Computer Science or Bioinformatics

– Master’s degree in Mathematics, Computer Science, or Bioinformatics.

– Skills in programming, algorithms, and preferably, experience with bioinformatics software.

– Ability to work in a multidisciplinary and collaborative research environment.