Two years postdoc position in geomatics: remote sensing and machine learning

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There is a vacancy for a postdoctoral researcher in the Geomatics research group of the Department of Civil Engineering of KU Leuven. The postdoc will be active in projects that aim at the processing and interpretation of remote sensing data from a wide range of sensors and platforms for different applications, such as Land Use and Land Cover (LULC) mapping, 3D reconstruction and buildings and infrastructure damage assessment. The position starts October 1st 2022 and is for two years.

The Geomatics group’s laboratory is based on the Technology Campus in Ghent, which is located at the center of Belgium, in the heart of Europe. The research group targets practical applications in the field of construction and surveying and focuses on data capture, processing and interpretation for the creation of semantically rich databases (i.e. BIM and GIS) and the analysis of the built environment. The emphasis is on the processing of geometry such as point cloud data and mesh data, and on information, extracted from imagery taken from the built environment.

The research at the Geomatics group, headed by prof. Maarten Vergauwen, is rapidly expanding. The group currently already has three postdocs and multiple PhD students, both working on individual research topics and international projects. In particular, related to this project, there is expertise in machine learning for geospatial applications, remote sensing, and the creation of intelligent databases. The research group also has strong ties to the industry and the research community. Within KU Leuven the group has contacts, relevant to this project, with the Departments of Electrical Engineering (ESAT), Computer Science and the other groups within Civil Engineering, and externally with project partners such as CERTH, UPF and the University of Liège. The group’s laboratory is well equipped with state-of-the art Lidar and photogrammetric hard and software and powerful processing units which the candidate can use for research.


  • You will work on the group’s projects about LULC analysis and pathology recognition in buildings and infrastructure. You will conduct the necessary research for these projects and manage them. This entails co-supervision of other collaborators of the project, as well as communication to the project partners and construction stakeholders.
  • You will develop general (machine learning and deep learning) methods to identify and segment elements in remote sensing data. You will apply these to analyze land use and detect material properties in such data. You will develop methods to translate image information to BIM/GIS databases for the purpose of texturing, state analysis, pathology modeling, etc.
  • You will conduct your own research in other(sub-)projects, collaborating with and co-supervising PhD students. You will (co-)write project proposals to extend the group’s know-how in this field.
  • You will publish your research in high-level (A1) international, peer-reviewed journals.