Analysis, Design and Development of Federated Learning Algorithms and Secure Aggregation Strategies for Edge-Based Industrial Digital Twin Platforms.
Deadline: 27/03/2026
Scientific-Disciplinary Group
01/INFO-01 - Informatics
Description
The assignment concerns the development and testing of advanced Federated Learning algorithms and secure aggregation strategies for artificial intelligence models within the FLINT – Federated Learning for INdustrial Twins platform. The research activity will be aimed at the study, implementation and validation of distributed learning solutions for edge-based environments, with particular attention to the management of heterogeneous data, the robustness of federated models, and the protection of privacy through secure aggregation and differential privacy techniques.
Job posting website
https://www.unina.it/it/ateneo/concorsi-e-borse-di-studio/incarichi-di-ricerca
Funding body
progetto FLINT, CUP B69J25001080005
How to apply
dip.matematica-app@pec.unina.it
View the original posting on the MUR website: Go to MUR website