Pica Code IR-2026-097 Model Merging for Federated Learning in Computer Vision

Italian Ministry of Education, University and Research; Italia; On-site; EUR 45,000 - 60,000; Full time

Job summary

Unimore is seeking researchers for advanced work on Model Merging techniques for Deep Learning models applied to Computer Vision tasks within Federated Learning settings. The role emphasizes Parameter-Efficient Fine-Tuning and full fine-tuning regimes, located in Italy and aligned with EU research standards.

The fellowship targets recognized researchers (R2–R4) with a priori qualifications and a selective public procedure based on qualifications and interviews.

Qualifications

• Research and implementation of Model Merging techniques for Deep Learning models in Computer Vision settings.

Responsibilities

• Selective public procedure based on qualifications and interview.

Job description

Organisation/Company Unimore Research Field Engineering » Computer engineering Researcher Profile Recognised Researcher (R2) Leading Researcher (R4) First Stage Researcher (R1) Established Researcher (R3) Application Deadline 18 Nov 2026 - 13:00 (UTC) Country Italy Type of Contract To be defined Job Status Not Applicable Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No

Offer Description

Research and implementation of Model Merging techniques for Deep Learning models applied to Computer Vision tasks in Federated Learning settings, addressing both Parameter-Efficient Fine-Tuning (PEFT) and full fine-tuning regimes.

• Italy

Eligibility of fellows: country/ies of residence:

• OTHER

Eligibility of fellows: nationality/ies:

• OTHER

Selection process

selective public procedure based on qualifications and interview