Postdoctoral position in machine learning at ENS Lyon
Applications are invited for a postdoctoral fellowship at ENS Lyon in the field of machine learning.
The position is part of the research project Neural networks for homomorphic encryption, funded by Inria. Fully homomorphic encryption (FHE) enables computations to be performed directly on encrypted data without knowledge of the deciphering key, offering significant potential for privacy-preserving deep learning. However, conventional neural networks are not well-suited to the computational constraints of FHE. The project aims to develop more efficient neural network architectures tailored for encrypted computations.
The project is coordinated by Jean-Christophe Mourrat, in collaboration with Guillaume Hanrot and Damien Stehlé (currently affiliated with Cryptolab in Lyon while on leave from ENSL), as well as Aurélien Garivier, Rémi Gribonval and the Inria Ockham team.
The position is for two years, with a possible extension of up to two additional years. The ideal start date is September 1, 2025. The fellowship includes financial support for conference travel and collaborator visits. There are no teaching obligations, though teaching opportunities can be arranged if desired.
Candidate Profile
The ideal candidate should have experience with machine learning, particularly in deep learning or related areas. No prior knowledge of cryptography is required. Expertise in mathematical analysis, optimization, or efficient algorithm design will be considered an asset.
Application process
Applications should include a CV, a list of publications and a research statement, and should be sent to jean-christophe.mourrat (α) ens-lyon.fr before March 14, 2025. Applicants should also arrange for two or three letters of recommendation to be sent directly to the same address.
Contact
For further inquiries, please contact Jean-Christophe Mourrat at jean-christophe.mourrat (α) ens-lyon.fr.
Updates
Feb. 20: the deadline for submitting an application has been postponed to March 14, 2025.