Artificial Intelligence Methodologies for the Analysis and Interpretation of 3D Data

10 ott - Roma
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Organisation/Company University of Macerata Research Field Technology » Dating techniques Researcher Profile First Stage Researcher (R1) Positions Other Positions Application Deadline 28 Oct 2026 - 13:00 (Europe/Rome) Country Italy Type of Contract Temporary Job Status Full-time 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 will focus on the study, development and validation of Artificial Intelligence methodologies for the processing, analysis and interpretation of three-dimensional data. Machine learning and deep learning techniques will be investigated for classification, semantic segmentation, object and structure recognition, automatic extraction of geometric and semantic features, and 3D scene understanding. The research will also address methodologies for integrating heterogeneous 3D data, assessing model reliability and robustness,



and exploiting multimodal approaches and foundation models for semantic enrichment and automated interpretation of three-dimensional information.
- PhD in Civil Engineering, Building Engineering-Architecture, Geomatics, or related fields.
- Proven research experience in 3D modelling and 3D point cloud processing, management, and analysis.
- Experience in the acquisition and processing of 3D data through photogrammetry, laser scanning, or other 3D surveying techniques.
- Scientific publications in international journals or conferences indexed in Scopus/WoS.
- Experience in applying Computer Vision, Machine Learning, or Artificial Intelligence methods to 3D data, point clouds, or geospatial data.
- Skills in software and tools for 3D modelling, point cloud processing, BIM/HBIM, GIS, and spatial data management.
- Experience in interdisciplinary research projects, collaborations with public bodies or companies, or technology transfer activities.

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