We are seeking a talented Master’s or PhD student in Computational Biology or Bioinformatics to join our Translational and Integrative Pathology Lab, investigating the molecular and spatial landscape of neuroendocrine lung neoplasms. The successful candidate will contribute to a cutting-edge project focused on Diffuse Idiopathic Pulmonary Neuroendocrine Cell Hyperplasia (DIPNECH)—a rare and understudied precursor lesion that can evolve into carcinoid tumors.

Leveraging spatial transcriptomics, deep genomic profiling, and tumor microenvironment (TME) analysis, this role will help uncover the clonal evolution and molecular mechanisms driving disease progression. The position offers a unique opportunity to work with high-resolution spatial omics data and contribute to impactful discoveries in lung cancer biology.

Laboratoire : Laboratoire de Bioinformatique et Protéomique (ADLab) – Pr. Arnaud Droit. Le laboratoire est spécialisé dans le développement de méthodes computationnelles avancées et d’approches d’intelligence artificielle et statistiques pour l’analyse de données massives. ADLab collabore avec des partenaires académiques et industriels à l’échelle internationale et dispose d’infrastructures de calcul de haut niveau.

Institution : Faculté de Médecine, Université Laval, Québec, Canada

Description du poste :
Le laboratoire du Pr. Arnaud Droit (ADLab) recrute un(e) étudiant(e) en bioinformatique pour travailler sur l’analyse de données de protéomique issues de spectromètres de masse de dernière génération. Cette recherche s’effectuera dans le cadre de la lutte contre l’antibiorésistance, qui représente une menace majeure pour la santé publique. Cette problématique est la conséquence de la surutilisation des antibiotiques qui favorise l’émergence de bactéries résistantes, rendant de nombreuses infections difficiles à soigner. Il est ainsi crucial de développer de nouvelles approches pour détecter et contrer ces résistances. Le ou la candidat(e) contribuera ainsi au développement d’outils informatiques pour l’analyse et la validation de données protéomiques ainsi qu’à l’application de méthodes d’apprentissage automatique pour l’identification de biomarqueurs diagnostiques dans des fluides biologiques (détection de bactéries, résistance aux traitements, etc.).

This fellowship (offering $35K-$50K annually) is offered to work on developing computational algorithms in cancer and epigenetics. Potential projects range from data analysis to deep-learning algorithms. Learn more about our research at:

https://panchenko-lab.org/

Available PhD programs:

• Pathology PhD Program
• Computer Science PhD Program
• Biochemistry & Molecular Sciences PhD Program

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.

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