Innovative technologies and methodologies for sustainable resource management and raw material valorization in the circular economy

Italian Ministry of Education, University and Research; Italia; On-site; EUR 42,000 - 64,000; Full time

Job summary

The Dipartimento ingegneria chimica materiali ambiente invites applications for a research position in CEAR-02/C – Raw Materials Engineering. The project focuses on developing methodologies for characterization, classification and sorting of primary and secondary raw materials, waste and process residues.

Non-destructive sensing and imaging techniques such as hyperspectral imaging, XRF and FTIR will be used; data will be analyzed with statistical, chemometric, and AI methods to support circular

Qualifications

• Eligibility of fellows: EU/Europe residents.

Responsibilities

• Develop methodologies for characterization, classification and sorting of raw materials and residues.
• Monitor environmental matrices and contaminants using non-destructive sensing techniques.
• Apply statistical, chemometric and AI methods for material recognition and recovery strategies.

Tools

Hyperspectral imaging

X-ray fluorescence

FTIR spectroscopy

Machine learning

Job description

Organisation/Company Dipartimento ingegneria chimica materiali ambiente Research Field Engineering » Industrial engineering Researcher Profile Recognised Researcher (R2) Leading Researcher (R4) First Stage Researcher (R1) Established Researcher (R3) Application Deadline 7 Nov 2026 - 23:59 (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

The research activity, within the scientific field CEAR-02/C – Raw Materials Engineering, will focus on the development of methodologies for the characterization, classification and sorting of primary and secondary raw materials, waste and process residues, as well as for the monitoring of environmental matrices and contaminants. Non-destructive sensing and imaging techniques will be employed, with particular reference to hyperspectral imaging (HSI), X-ray fluorescence (XRF) and (micro)FTIR spectroscopy. Acquired data will be processed using statistical and chemometric methods, machine learning and artificial intelligence for material recognition and classification and the identification of contaminants and recoverable components. The developed methodologies will be applied to resource recovery and valorization, recycling, environmental monitoring and remediation, in accordance with circular economy principles.

• Italy

Eligibility of fellows: country/ies of residence:

• EUROPE