LLM based Digital Twin for Asset and Facility Management - 2026_IDR_DABC_9

Organisation/Company Politecnico di Milano Research Field Engineering Researcher Profile Recognised Researcher (R2) Leading Researcher (R4) First Stage Researcher (R1) Established Researcher (R3) Application Deadline 10 Nov 2026 - 12:00 (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

Digital Twins (DTs) integrate sensor-generated data with geometric, semantic, and contextual information from Building Information Modelling (BIM), supporting the management and maintenance of buildings and infrastructure. However, their adoption in Asset and Facility Management (A&FM) is often constrained by the complexity of accessing and interpreting heterogeneous data.
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This research will investigate the use of Large Language Models (LLMs) as natural-language interfaces to Digital Twins, enabling users to access and interpret data without advanced technical expertise. xysqume It will develop and validate an LLM-enabled framework to transform Digital Twin data into actionable information supporting operational and strategic decision-making.

Relevance and pertinence of the publications, theses and scientific products attached to the research programme covered by the Fellowship (up to 30 points)

Relevance and pertinence of previous research activities and work experience, if any, in relation to the research activity covered by the Fellowship (up to 60 points)

Relevance and pertinence of their study programme to the research programme covered by the Fellowship (up to 10 points)

• EUROPE

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• All

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