Postdoctoral student in bioinformatics

The laboratory of Dr. Arielle Elkrief, co-Director of the CHUM Microbiome Centre is searching for a talented and self-driven Computational Biologist or Bioinformatician to join our computational team as a post-doctoral fellow. The candidate will focus on establishing computational infrastructure for analysing complex and multimodal microbiome data. The candidate will be working closely with other computational biologists, basic scientists, students, and researchers including members of the Dr. Bertrand Routy laboratory, co-Director of the CHUM Microbiome Centre.

The Elkrief lab will provide both computational support with a senior computational biologist on-staff. The candidate will be responsible for designing a data architecture to leverage and integrate in house microbiome-oncology datasets, processing, visualizing and interpreting data for multiple projects.

The lab focuses on developing novel microbiome-based therapies for people with lung cancer and melanoma treated with immunotherapy. This includes investigating the role of fecal microbial transplantation, probiotics, prebiotics, and diet in prospective clinical patient trials, with a focus on integrating multi-omic translational correlative approaches using biospecimens from patients enrolled on these trials. The specific role of the candidate will be to perform primary computational biology analyses on samples from multiple clinical trials with high potential for impact.

• Raw processing, analysis, and visualisation of fecal metagenomics and 16s rRNA data (human and murine)
• Transkingdom representation of clinical, dietary, metagenomic, metabolomic, and immunologic multi-omic data
• Data infrastructure organization
• Implement and follow the best practices in data management and data architecture

• A Ph.D. or M.D./Ph.D. in bioinformatics, computational biology, computer science, or related field
• Training in or experience in metagenomics processing, statistical analysis, and visualisation
• Proficiency in R or python and command-line programming languages
• Proficiency in using computing cluster tools
• Expertise in data management, and architecture
• Strong problem-solving abilities and resilience in a fast-paced, dynamic environment
• Ability to collaborate and communicate effectively with team members and external stakeholders
• Ability to multitask and lead analyses for multiple projects