M2 internship in bioinformatics and systems immunology

 Stage · Stage M2  · 6 mois    Bac+5 / Master   i3 Lab, UMRS959, Sorbonne University · Paris 13 (France)  15 % du plafond horaire de la sécurité sociale (4,35 €/h en 2025)

 Date de prise de poste : 1 janvier 2026

Mots-Clés

regulatory T cells (Tregs) T-cell receptor (TCR) Bioinformatics Machine Learning RNA-seq artificial intelligence systems biology Immunology NGS autoimmunity Data Mining Clustering Pipeline

Description

TCR Metaclonotype Discovery in Autoimmune Diseases

Name: UMRS 959 “Immunorégulation-Immunopathologie-Immunothérapie”

Affiliation: Inserm / Sorbonne Université

Address: Hôpital Pitié-Salpêtrière, 83 boulevard de l’hôpital, Bâtiment CERVI, 4ème étage, 75013 Paris

Website:
https://www.i3-immuno.fr/en/#Research
https://qimmuno.com/research/

Supervisors:
Encarnita Mariotti-Ferrandiz (encarnita.mariotti@sorbonne-universite.fr)
Andreas Tiffeau-Mayer (andreas.mayer@ucl.ac.uk)

Subject keywords:
Autoimmunity; Regulatory T cells (Tregs); T effector cells (Teffs); T cell receptor (TCR); Deep sequencing; Bioinformatics; Data mining; Machine learning; Systems immunology; Immunopathology; Biomarker discovery

Tools and methodologies:
High-throughput TCR repertoire sequencing; Bioinformatics pipelines (Metaclonotypist); Unsupervised clustering; Statistical modeling; Machine learning; Data integration and visualization

Summary of lab’s interests:
This project is an opportunity to join an interdisciplinary collaboration between the i3 laboratory (Sorbonne Université) and the q-immuno lab (University College London). The i3 laboratory is using systems immunology approaches to identify novel biomarkers for diagnosis and therapy with a particular focus on Treg biology and autoimmune disorders (AD). The laboratory has been leading a comprehensive effort at profiling T cell receptor (TCR) repertoires in AD using deep sequencing. The q-immuno lab studies the molecular rules of TCR specificity and develops computational tools to sensitively identify antigen-specific TCR motifs in sequencing data.

Summary of the proposed project:
The balance between regulatory T cells (Tregs) and self-reactive T effector cells (Teffs) underlies immune homeostasis, and its deregulation can lead to AD. T cell antigen-specificity is determined by their TCR, and repertoire sequencing thus provides a promising source of potential biomarkers as well as novel therapeutics targets for AD.

The i3 lab has sequenced TCR repertoires from peripheral blood Tregs and Teffs across 600 AD patients and healthy donors (Transimmunom (NCT02466217) and LUPIL-2 trial (NCT02955615)). The q-immuno lab has developed a bioinformatics pipeline for the accurate and scalable discovery of TCR metaclonotypes, clusters of TCRs with likely shared antigen specificity, in TCR repertoires.

The aim of this project is to discover Treg and Teff metaclonotypes associated with autoimmune disease and clinical outcome. Clustering overcomes the vast diversity of TCRs created by VDJ recombination, and thus extends biomarker discovery beyond direct comparisons to the most public TCRs. The project will involve adapting Metaclonotypist to the AD datasets, and optimizing parameter choices for this novel application context. Unravelling the antigen-specificity of Tregs and Teffs in AD is important in order to (i) better understand AD development and outcome, (ii) identify biomarkers and (iii) develop new therapeutic strategies.

Candidate profile:
The ideal candidate will have training in computational biology and/or machine learning, with a strong interest in immunology. The candidate will be responsible for extending and refining the computational pipeline, performing data analysis, and contributing to the biological interpretation of findings.

Lab description:
The i3 laboratory offers a uniquely interdisciplinary environment integrating computational biologists, immunologists, physicists, computer scientists, and clinicians. The candidate will be based in the i3 laboratory on the Pitié-Salpêtrière hospital campus in Paris (13ème) and co-supervised by Andreas Tiffeau-Mayer at University College London.

Publication supervisors (related to the project):
Jouannet et al., bioRxiv, 2024
Mhanna V. et al., Nat Rev Methods Primers, 2024
Mhanna V. et al., Cell Rep Methods, 2024
Le Gouge et al., MedRxiv, 2023
Quiniou V. et al., eLife, 2023
Mhanna V. et al., Diabetes, 2021
Barennes P. et al., Nature Biotechnologies, 2020
Nagano Y. et al., Cell Systems, 2025
Turner C.T. et al., bioRxiv Preprint, 2025

Candidature

Procédure : Envoyer un mail à encarnita.mariotti@sorbonne-universite.fr et andreas.mayer@ucl.ac.uk

Date limite : 31 décembre 2025

Contacts

 Encarnita Mariotti-Ferrandiz
 enNOSPAMcarnita.mariotti@sorbonne-universite.fr

 Andreas Tiffeau-Mayer
 anNOSPAMdreas.mayer@ucl.ac.uk

Offre publiée le 21 octobre 2025, affichage jusqu'au 31 décembre 2025