MSc or PhD Student – Computational Biology / Spatial Transcriptomics

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.

• Analyze and integrate multi-modal datasets including spatial transcriptomics (Visium HD, Xenium), 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, with experience using packages such as Seurat, Scanpy, Bioconductor, or similar.
• Hands-on experience with spatial omics technologies (e.g., Visium, Xenium, CosMx, GeoMx, PhenoCycler-fusion) is highly desirable.
• Familiarity with lung cancer biology, neuroendocrine tumors, or TME analysis is a strong asset.
• Strong problem-solving skills and ability to work independently and collaboratively.
• Excellent written and verbal communication skills (English and/or French).