PhD Position in Bioinformatics / Spatial Omics – Québec City (Sept 2026)

We are seeking an outstanding and highly motivated PhD student in Computational Biology or Bioinformatics to join the Translational and Integrative Pathobiology Lab (LCTIP‑Lab) in Québec City. This position offers a unique opportunity to work at the forefront of spatial omics, tumor microenvironment (TME) biology, and multimodal data integration, under the co‑supervision of Dr Philippe Joubert and Dr Fabien Lamaze.

The PhD project focuses on Diffuse Idiopathic Pulmonary Neuroendocrine Cell Hyperplasia (DIPNECH)—a rare and poorly understood precursor lesion that can progress to pulmonary carcinoid tumors. This understudied disease context provides a rare opportunity to make first‑in‑field discoveries with strong translational relevance.

By leveraging spatial transcriptomics, deep genomic profiling, and TME‑focused analyses, the successful candidate will investigate clonal evolution and molecular mechanisms driving disease progression at high spatial resolution. The project is designed to generate impactful insights into lung cancer biology while providing rigorous training in advanced computational and analytical methods.

Research Environment & Resources

The successful candidate will work with state‑of‑the‑art spatial and single‑cell platforms, including:

• Visium HD
• Xenium
• PhenoCycler‑Fusion
• CyTOF

These technologies are rarely available together within a single PhD project. The lab provides access to deeply annotated clinical, histological, and genomic datasets, and fosters a highly collaborative environment bridging pathology, genomics, computational biology, and machine learning.

Strong mentorship is provided in:

• Computational and statistical methods
• Cancer and TME biology
• Scientific writing, presentations, and academic career development

• Analyze and integrate multi-modal datasets including spatial omics profiling, bulk RNA-seq, single-cell RNA-seq, and IHC.
• Develop and maintain reproducible bioinformatics pipelines for spatial data processing and visualization.
• Perform differential expression, trajectory inference, cellular neighborhood, and cell-cell interaction analyses.
• Collaborate with pathologists, geneticists and wet lab scientists to interpret results and guide experimental design.
• Contribute to scientific publications, presentations, and grant proposals.
• Maintain organized documentation and ensure data integrity and reproducibility.

• BSc or MSc in Bioinformatics, Computational Biology, Genomics, or a related field
• Proficiency in R and/or Python
• Experience with single‑cell or spatial analysis frameworks (e.g., Seurat, Scanpy)
• Hands-on experience with spatial omics technologies (e.g., Visium, Xenium, CosMx, GeoMx, PhenoCycler-fusion) is highly desirable
• Interest in cancer biology, spatial omics, and integrative data analysis
• Strong problem-solving skills and ability to work independently and collaboratively
• Excellent written and verbal communication skills (English and/or French)