Ph.D. position in Computational Cancer Genomics

Offered jointly by Cancer Genomics and Computational and Statistical Genomics labs at McGill University and Genome Quebec Innovation Centre

Understanding interactions between genomic repertoires of tumor cells

and host immune reactions

Immunotherapies have shown promising results in cancer control; however, response to treatments varies between cancer types and even among patients affected with the same cancer. Genomics and transcriptome variations in tumor cells and their interactions with the host (i.e. patient) have been postulated to play major roles in this heterogeneity, but the underlying mechanisms are not known.

We apply quantitative genomics and bioinformatic approaches to large-scale genome and RNA sequencing data to investigate the immune landscapes of tumors, infer the activity patterns of tumor-infiltrating immune cells, and examine their relationship with the genomic characteristics of tumors. We further combine results from these analyses with dynamics of gene-regulatory programs in cancer to predict interactions between master regulators of cancer transcriptome and immune system reactions. These predictions are then examined using functional experiments including gene perturbation in cancer models and high-content imaging assays that provide full resolution maps of tumor-immune cell interactions.

Candidate students: Applicants should have a practical experience in quantitative biology approaches including statistical genetics and be familiar with computational approaches to large datasets. Preference will be given to candidates who have background knowledge in cancer genomics.