PhD or postdoc in Computational Phylogenetics with Applications to Virus Evolution

vor 2 Wochen


Wädenswil, Zürich, Schweiz Zurich University of Applied Sciences (ZHAW) Vollzeit

Job Tasks:

  • The evolutionary history of molecules is described by a tree structure called phylogeny, which is inferred from genomic sequences.
  • Phylogenies are used for testing biological hypotheses with applications ranging from medicine to ecology.
  • To improve the reliability of phylogenetic analyses, we develop methods to address this apparent circularity.
  • We have made a recent breakthrough enabling joint inferences using a likelihood-based method based on a single residue insertion-deletion process.
  • We aim to develop a new maximum likelihood method for scalable joint inference of the complete evolutionary history (alignment, tree, ancestral sequences) under more realistic models that allow multiple residue insertions and deletions.
  • An integral part of the research is to apply the methods to real data, notably, Swiss HIV Cohort.
  • The project is funded by the Swiss National Science Foundation.

Position Details:

The positions are based at the Institute of Computational Life Sciences, Zurich University of Applied Sciences (ZHAW Wädenswil). The PhD student will also be enrolled at the University of Zurich. The research group is also part of Swiss Institute of Bioinformatics, which provides additional training and networking opportunities.

A Selection of Relevant Articles:

  • Maiolo M, Zhang X, Gil M, Anisimova M. "Progressive multiple sequence alignment with indel evolution" BMC Bioinformatics :331. doi: /s
  • Pečerska, J., Gil, M. and Anisimova, M. "Joint alignment and tree inference" bioRxiv, 2021. pp doi: /
  • Jowkar, G., Pečerska, J., Maiolo, M., Gil, M., & Anisimova, M. "ARPIP: Ancestral sequence Reconstruction with insertions and deletions under the Poisson Indel Process" Systematic biology syac050-syac050. doi: /sysbio/syac050

Profile Requirements:

  • Strong background in computational science, algorithms, programming, statistics, stochastic modeling or similar;
  • Working knowledge of C++ and/or Rust;
  • Some knowledge of phylogenetics and molecular evolution is an advantage.


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