Jobs
17 days ago
Queen's University -
This fellowship (offering $35K-$40K annually for four years) is offered to work on developing computational algorithms in cancer and epigenetics. The potential projects range from data analysis to developing deep-learning algorithms. Learn more about our research at:
Available PhD programs:
22 days ago
Canada's Michael Smith Genome Sciences Centre at BC Cancer -
Canada’s Michael Smith Genome Sciences Centre (GSC)
Today’s Research. Tomorrow’s Medicine.
The GSC is a department of the BC Cancer Research Institute and a high-throughput genome sequencing facility. We are leaders in genomics, proteomics and bioinformatics in pursuit of novel treatment strategies for cancers and other diseases.
Among the world’s first genome centres to be established within a cancer clinic, for more than two decades our scientists and innovators have been designing and deploying cutting-edge technologies to benefit health and advance clinical research.
Among the GSC’s most significant accomplishments are the first publication to demonstrate the use of whole-genome sequencing to inform cancer treatment planning, the first published sequence of the SARS coronavirus genome and major contributions to the first physical map of the human genome as part of the Human Genome Project.
By joining the GSC you will become part of an exceptional and diverse team of scientists, clinicians, experts and professionals operating at the leading edge of clinical research. We look for people who share our core values—science, timeliness, respect—to join us on our mission to use genome science for the betterment of health and society.
Summary
Job Reference No. RA_R00006_Clinical_2025_01_10
Canada’s Michael Smith Genome Sciences Centre (GSC) of the BC Cancer Research Institute is a state-of-the-art, large-scale, high-throughput, clinically accredited genomics and bioinformatics facility located in one of the most vibrant and diverse cities in the world.
As a Research Associate within the Centre for Clinical Genomics Informatics team at the GSC, you will play a pivotal role in advancing clinical bioinformatics capabilities by developing, validating, and optimizing workflows and pipelines to support cutting-edge genomic technologies. The Research Associate will report to the Team leader and is anchored within a team of exceptional computational scientists, programmers and clinical researchers, who collaborate directly on the development and maintenance of robust, cost efficient, and competitive clinical genomics pipelines.
This is an opportunity to work with highly motivated colleagues in a science-oriented, creative and dynamic environment. We offer a competitive salary, excellent benefits and significant career development opportunities.
This position is initially funded for two years.
32 days ago
Université de Sherbrooke -
Project Background.
We are seeking a motivated PhD student to join our research team in developing advanced methods for phylogenetic network analysis, with a specific focus on network consensus algorithms. Significant progress has been made in consensus tree methodologies. A consensus tree is a phylogenetic tree that synthesizes multiple phylogenetic trees, each with the same leaf labels but possibly differing topologies. These trees are often generated through bootstrapping or other sampling techniques. Traditional approaches to consensus tree construction focus primarily on topological aspects, often overlooking the importance of branch length, which captures the temporal progression of genetic mutations. However, in the context of consensus networks, very few studies have introduced relevant concepts.
Project Objective.
Our project addresses this limitation by integrating branch-length data not only into the construction of consensus trees but also into network consensus construction. This more comprehensive approach aims to provide a richer and more accurate representation of evolutionary relationships by combining topological structure, branch frequency, clade frequency, and branch length.
The candidate must hold a Master’s degree in Mathematics, Computer Science, or Bioinformatics with a strong overall GPA.
Compensation: non-taxable scholarship of +20,000 CAD per year.
To apply, please send your CV, list of peer-reviewed articles (optional), and a cover letter to: Prof. Nadia Tahiri
32 days ago
Université du Québec à Montréal, Département d’Informatique -
Le projet est mené par une équipe multidisciplinaire de l’Université du Québec à Montréal (UQAM) (Prof. Vladimir Makarenkov), de l’Université de Sherbrooke (Prof. Guillaume Blanchet et Prof. Nadia Tahiri) et de l’Université de Montréal (Prof. Pierre Legendre).
Ce type de structures en réseau doit permettre une analyse plus souple et complète des données génomiques et métagénomiques, surpassant les limitations des méthodes actuelles basées sur les arbres et réseaux phylogénétiques.
L’objectif principal de notre projet est de développer des méthodes informatiques et mathématiques pour analyser de grands jeux de données biologiques et bioinformatiques via des réseaux de similarité.
43 days ago
Centre du Recherche du CHU de Québec - Université Laval -
Laboratory: Bioinformatics and Proteomics Laboratory (ADLab) – Prof. Arnaud Droit. The laboratory specializes in the development of advanced computational methods and artificial intelligence and statistical approaches for the analysis of massive datasets. ADLab collaborates with academic and industrial partners internationally and has high-performance computing infrastructure. Institution: Faculty of Medicine, Université Laval, Quebec City, Canada
Job Description: Prof. Arnaud Droit’s laboratory (ADLab) is recruiting a bioinformatics student to work on the analysis of proteomics data generated by latest-generation mass spectrometers. This research will be conducted as part of the fight against antibiotic resistance, which represents a major threat to public health. This issue is a consequence of the overuse of antibiotics, which promotes the emergence of resistant bacteria, making many infections difficult to treat. It is therefore crucial to develop new approaches to detect and counter these resistances. The candidate will contribute to the development of computational tools for the analysis and validation of proteomics data, as well as the application of machine learning methods for identifying diagnostic biomarkers in biological fluids (detection of bacteria, treatment resistance, etc.).