Postdoctoral Fellow in the Evolution of Wildlife-associated Coronaviridae

A funded Postdoctoral Fellow opportunity is available in Dr. Finlay Maguire’s group in the Computer Science / Community Health & Epidemiology at Dalhousie University.

This is a full-time one-year position, with the possibility of extension, at the University of Dalhousie. This position is supported by a New Frontiers in Research Fund Explore grant with Dr. Samira Mubareka at Sunnybrook Research Institute/University of Toronto, Dr. Arinjay Banerjee at the Vaccine and Infectious Disease Organisation/University of Saskatchewan, and Dr. Jeff Bowman at Ontario Ministry of Natural Resources/University of Trent.

The successful applicant will lead computational work in the Maguire lab to characterise the evolution, diversity, and function of accessory genes in Alpha- and Betacoronavirus species (CoVs) associated with wildlife infections. Building on prior work with wildlife-associated SARS-CoV-2 and endemic CoVs, this project seeks to characterise the ecological features of viral activity in specific wildlife hosts, the breadth and distribution of genetic diversity for endemic CoVs, and the principle molecular drivers of their evolution. This will be achieved by mining large–scale sequencing datasets (and our own samples) for the genomes of wildlife-associated CoVs and then characterising the accessory gene mutational and selection landscape using phylogenetic, coupling/autoencoder models, structural prediction, and machine learning approaches. These results will be used to inform concurrent wildlife cell-line/organoid–based experimental work in the Mubareka (Toronto) and Banerjee labs (VIDO).

The successful candidate will also have the opportunity to work with a multi-institutional team of experts in epidemiology, bioinformatics, virology, immunology and human and animal health through the Wildlife-Emerging Pathogen Initiative (https://wildepi.ca).

Subject to negotiation, there is a possibility of remote employment within Canada.

The ideal candidate will have strong oral and written communication skills, the ability to work independently and as a part of a team, and proven experience with bioinformatics (including genomics and phylogenetics) and predictive statistical or machine-learning modelling. Programming experience in Python or R is essential for this position. Prior experience with viral data is desirable. Selection of the successful candidate will be based on a combination of academic excellence, relevant experience, career goals, and referee assessments.