Offre en lien avec l’Action/le Réseau : – — –/Doctorants

Laboratoire/Entreprise : LS2N
Durée : 3 year
Contact : hala.skaf@univ-nantes.fr
Date limite de publication : 2025-12-22

Contexte :
I am seeking excellent candidates for a fully funded 3-year Phd position funded by the ANR SaFE-KG project.
Goal: Formalise, design, and implement a secure, efficient federation engine enabling LLM-like querying across sensitive biomedical knowledge graphs, with fine-grained access control and provenance.

Sujet :
In the context of SaFE-KG, the main objectives of the thesis is to design and implement an Efficient and Secure Federation Engine able to:

Query decentralized knowledge graphs under fine-grained access control policies.
Ensure high performance and scalability in secure federations.
Interact with LLM to support query building
Return results enriched with provenance and usage control information.
Support adaptive query processing techniques, including secure sampling.

Profil du candidat :
Solid background in Semantic Web, knowledge graphs, SPARQL; familiarity with sampling and/or ML/LLMs is a plus.

Formation et compétences requises :
Master’s in CS/IS (strong ranking).

Adresse d’emploi :
LS2N, Nantes Université

Document attaché : 202509221432_SujetThèse-Safe-KG-5.pdf