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

id="offer-description" class="ecl-u-type-heading-2 ecl-u-mt-none ecl-u-mb-l">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. Where to apply Website https://www.unimore.it/it . Requirements. Additional Information . Eligibility criteria. Eligible destination country/ies for fellows: . 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. Additional comments. Contact email: [email protected] . Contact phone: 059/2056447-6075-7078. Annual budget: 27.754. Frequency of calls: 12. International mobility required: no. Website for additional job details https://titulus-unimore.cineca.it/albo/. <h2