PhD 01 - Digital product passport and data integration for circular refractory raw materials and industrial applications A 36 Months PhD starting in October 2026
and supervised between
ULIEGE (Belgium)
and
RHIM-Leoben (Austria) Objectives PhD01 will define and implement a Digital Product Passport tailored to refractory raw materials, including both primary and recycled materials. The purpose is to make information such as composition, processing history, performance indicators and provenance machine-readable and interoperable with industrial plant systems and digital twin environments. The project will build a demonstrator populated with data from recycling hubs and automated sorting systems for brick and monolithic ladle linings. It will also identify data gaps and develop artificial intelligence-based strategies to estimate missing values, while keeping uncertainty transparent and auditable. The work will ensure compatibility with the semantic data platform developed in Work Package 1 and with the predictive tools developed in Work Package 3, so that environmental indicators from Life Cycle Assessment and operational key performance indicators can circulate across design, production, use and end-of-life stages. Expected Results The project will deliver a refractory-specific Digital Product Passport data model covering composition, processing history, performance indicators and provenance. It will also provide interoperability rules aligned with plant systems and digital twins, a demonstrator populated with real recycling and sorting data, integration guidelines, and a roadmap for deployment and standardisation. This will provide the project with a common digital traceability backbone for circular refractory value chains. Interaction with other PhD's PhD01 interacts closely with PhD02, PhD03 and PhD04, as it provides the traceability backbone that connects environmental assessment, cloud-based data integration and automated quality control. It also receives materials-related information from the refractory development projects and operational performance information from the digital modelling and optimisation projects, helping create a common digital record across the full refractory life cycle. Short stay & secondment(s) Short stay (1 week) at Siemens to acquire an in-depth understanding of the database architecture developed in PhD03 and the data structures required to process the input data generated in PhD01. Organization of timeline Work contract timeline: Period 1 –
ULIEGE, Liège, Belgique (9 months) Period 2 –
RHI MAGNESITA, Leoben, Austria (18 months) Period 3 –
ULIEGE, Liège, Belgique (9 months) Work location timeline: Period 1 and period 3 –
ULIEGE, Liège, Belgium (9 months months per period) Period 2 –
RHI MAGNESITA, Leoben, Austria (18 months) Applicant Profile Master’s level in Materials Science and/or Computer Science or Big Data Engineering. Candidates should be excellent in their skills for developing an innovative DPP demonstrator including information coming from several fields along the value chain. Oral and written communication skills (English) are also required. Some experience in Python and/or C++ programming will be appreciated. Supervisors contact details ULIEGE Prof. Angélique LEONARD – a.leonard@uliege.be Dr. Sylvie GROSLAMBERT – s.groslambert@uliege.be RHI MAGNESITA Michael JOOS – michael.joos@rhimagnesita.com Dr. Thomas DRNEK – thomas.drnek@rhimagnesita.com Applications must be made via the forms on the recruitment procedure page. Relevant Publications Some examples of recent publications: Leitner, A., Neuhold, S., Heid, S., Gavagnin, D., Meschik, P.M., Stastny, R., Zocratto, B. and Naves Moraes, M. (2024) ‘Enhancing refractory recycling: The role of automated sensor-based sorting systems’, RHI Magnesita Bulletin, pp. 41–46. Available at: https://www.rhimagnesita.com/the-bulletin-blog/enhancing-refractory-recycling/. Psarommatis, F. and May, G. (2024) ‘Digital Product Passport: A pathway to circularity and sustainability in modern manufacturing’, Sustainability, 16(1), p. 396. Available at: https://doi.org/10.3390/su16010396. Demmler, D., Krupka, D. and Federrath, H. (2022) ‘Requirements for a Digital Product Passport to boost the circular economy’, INFORMATIK 2022, Lecture Notes in Informatics (LNI), pp. 1–10. Available at: https://doi.org/10.18420/inf2022_127. Badioli, S., Dargaud, M. and Léonard, A. (2025) LCA of recycling processes of refractory materials, with ecodesign recommendations. Deliverable 1.3. Available at: https://doi.org/10.5281/zenodo.17150998 Carminati, L., Arioli, V., Sala, S., Pirola, F. and Pezzota, G. (2026) ‘Towards effective implementation of digital product passports: stakeholders involved and data requirements’, in Mizumaya, H., Morinaga, E., Nonaka, T., Kaihara, T., von Cieminski, G. and Romero, D. (eds.) Advances in Production Management Systems: Cyber-Physical-Human Production Systems: Human-AI Collaboration and Beyond. APMS 2025. IFIP Advances in Information and Communication Technology, vol. 766. Cham: Springer. Available at: https://doi.org/10.1007/978-3-032-03538-7_38
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