Artificial Intelligence and Blockchain Methodologies for Traceability, Quality, and Safety in the Meat Supply Chain.

Università degli Studi di Napoli “Federico II\"; Italia; On-site; EUR 35,000 - 52,000; Full time

Job summary

Università degli Studi di Napoli “Federico II" in Naples invites applications for a PhD/First Stage Researcher (R1) position in the Department of Electrical Engineering and Information Technologies (DIETI). The project investigates AI and Blockchain methods to monitor and intelligently manage the meat supply chain, with data acquisition, integration, and certification across the chain.

Responsibilities include exploring smart contracts and distributed ledger technology to ensure traceability,

Job description

Organisation/Company Università degli Studi di Napoli “Federico II" Department Department of Electrical Engineering and Information Technologies (DIETI) Research Field Engineering » Electrical engineering Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 7 Dec 2026 - 12:00 (Europe/Rome) Country Italy Type of Contract Temporary Job Status Full-time Offer Starting Date 1 Jan 2027 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Reference Number RIF. DIETI POST DOC 12/2026 Is the Job related to staff position within a Research Infrastructure? No

Offer Description

The research activity aims to investigate and experiment with innovative methodologies based on the integration of Artificial Intelligence (AI) and Blockchain technologies for monitoring and intelligent management of the meat supply chain. Models and architecture will be investigated for the acquisition, integration, and certification of data generated throughout the different stages of the supply chain, from livestock farming and processing to product distribution. Blockchain technologies will be investigated as an infrastructure to ensure traceability, data integrity, transparency, and verifiability, including the use of smart contracts and distributed ledger mechanisms. In parallel, Artificial Intelligence and Machine Learning techniques will be studied for supply chain data analysis, with particular emphasis on anomaly detection, quality and safety indicator assessment, risk prediction, and decision support.

Further information regarding the public selection procedure and the forms required to apply can be found in the official call for applications, published on the institutional websites: