CHUSJ Research Centre and UdeM are committed to developing world-class expertise in this field. The researcher will also become a member of the IVADO (the Institute for Data Valorisation) data science community. The IVADO aims to bring together industry professionals and academic researchers to develop cutting-edge expertise in data science, operational research and artificial intelligence. IVADO members provide data management methods and inform decision making for optimal resource use. In essence, the IVADO creates opportunities for knowledge exchange and collaborations between the specialists, partners, researchers and students in its network.

The new principal investigator will play a pivotal role in complementing the research strengths of the CHUSJ Research Centre. The selected candidate will also be expected to join the newly formed Centre for Integrated Pediatric Clinical Genomics and contribute to its mission. Moreover, the candidate will have the opportunity to collaborate with other research groups within the network of the Faculty of medicine and IVADO. Montreal has one of the largest artificial intelligence communities in North America and it is a vibrant, international and welcoming city full of “joie de vivre”, with great food, diverse and creative musical and cultural scenes, and inspiring outdoors.

Specifically, outstanding applications are sought in the areas of:
•Computational biology with expertise in statistical machine-learning models for analysis big data.
•Development of fast and accurate optimization algorithms in different areas applied to biology and medicine including genomic and epigenomic data.
•Development of innovative approaches to analyze large-scale diverse data and high-throughput functional screens and/or use of state-of-the-art technologies to investigate the functional consequences of genomic variation in relevant models.

Such expertise will complement existing expertise within the CHUSJ Research Centre and the Faculty of Medicine, UdeM and markedly improve our understanding of biological processes underlying disease predisposition and prognosis, accelerating the identification of biomarkers for disease risk prediction models, and the development of novel strategies for prevention and treatment.