Description du sujet de thèse

Spatial transcriptomics approaches provide an unprecedented view of how cells are organized within their tissue environment. They allow the identification of cellular niches or “ecotypes” that play a major role in tumor dynamics and interactions with the microenvironment. Despite these advances, several methodological challenges remain: the very definition of a niche or multicellular neighborhood is still unclear, extracting relevant features from gene expression data remains complex, and the available studies for method validation are limited. Moreover, clinical applications of these approaches in oncology are still in their early stages.

This PhD project aims to characterize the cellular niches associated with different tumor cell subtypes in pancreatic adenocarcinoma (in particular the basal and classical phenotypes), using bulk spatial transcriptomics data from the ITMO Cancer ACACIA project and public datasets.

Contexte de travail

The Grenoble Computer Science Laboratory (LIG) is a major research center whose academic partners include Université Grenoble Alpes, Grenoble INP – UGA, CNRS, and Inria. The LIG brings together nearly 500 researchers, faculty members, PhD students, and research support staff. They come from different institutions and are distributed across the laboratory's three sites: the main campus, Minatec, and Montbonnot. The laboratory's ambition is to build on the complementary expertise and recognized excellence of its 22 research teams to contribute to the development of the fundamental aspects of computer science (models, languages, methods, algorithms) and to foster synergy between the conceptual, technological, and societal challenges associated with this field.

Le poste se situe dans un secteur relevant de la protection du potentiel scientifique et technique (PPST), et nécessite donc, conformément à la réglementation, que votre arrivée soit autorisée par l'autorité compétente du MESR.

Contraintes et risques

None