PhD Student

Last application date
Feb 01, 2022 00:00
TW07 - Department of Telecommunications and Information Processing
Limited duration
Master of Science in Computer Engineering, Computer Science, Mathematics, Informatics, Electrical Engineering, or similar
Occupancy rate
Vacancy type
Research staff

Job description

Imec-IPI is looking for a qualified and motivated PhD student to work on a new imec.ICON project on the topic of multi-camera algorithms and 3D reconstruction for construction site monitoring. One fully funded position as PhD student is available (4 years, with intermediate evaluation after one year).

You will contribute as researcher to the project “BIM on Building site” (BoB), funded by imec. This project is an interdisciplinary research project involving the research groups imec-IDLab and imec-IPI both from the Faculty of Engineering and Architecture and the companies Balloon Inc., D-studio, Willemen and Dethier. The BoB project aims to reduce the cost-overruns in the construction sector by providing a cost-efficient scalable solution for automated monitoring of construction sites by creating a link between real-time on-site progress data and BIM. The on-site progress will be captured using novel algorithms for 3D matching between video and 3D BIM data, combined with recognition of collective activities to obtain more fine-grained insight in the construction process (e.g. hours spent on braiding reinforcement or pouring concrete). This data will then be brought together in an integrated progress analysis solution and validated on several construction sites.

Specifically, you will design algorithms for highly-precise auto-calibration of camera networks with mixed overview-partial camera views. In addition, you will research spatio-temporal cross-modal 3D matching to link on-site camera images with 4D BIM models to estimate construction progress in highly challenging environments: presence of occlusion, clutter, varying weather conditions, etc.

We offer you the opportunity to do full-time research in a highly international and friendly working environment, with a competitive salary at Ghent University, in the context of an interdisciplinary research project. As a researcher within imec-IPI, you will publish your research results at major international conferences and in scientific journals in order to pursue your PhD degree. You will also assist in limited educational tasks of the research group. IPI provides ample opportunity for researchers to take initiative in their work and to develop their professional networks.

Image Processing and Interpretation (IPI, is an imec research group at Ghent University. IPI consists of 40 researchers and conducts state of the art research in the field of digital image and video processing for a wide range of applications including real-time image and video processing, and machine learning, covering a wide range of application domains, including industrial inspection, (ultra) high-definition video improvement, smart multi-camera networks, mobile mapping, real-time vision and sensor fusion, and medical imaging.

Ghent University ( consistently ranks among the best 100 universities in the world, including, 69th by the Academic Ranking of World Universities (or Shanghai ranking) and 88th by U.S. News & World Report. The IPI Lab is location on the university’s UFO campus in the center of Ghent, Belgium, a city recently rated as one of the best places to visit in Europe for culture (

Job profile

  • You hold a relevant master’s degree (e.g. Master of Science in Computer Engineering, Computer Science, Mathematics, Informatics, Electrical Engineering, or similar) with demonstrated first-class performance (e.g., outstanding grades, thesis result, or publications).
  • You can demonstrate mastery of core aspects of machine learning and image processing:
    • Image representation, registration, filtering, denoising, normalization, morphology
    • Image analysis, classification, object tracking
    • (Deep) neural networks, (un-)supervised learning, decision trees, dimensionality reduction, overfitting, etc.
    • Design of algorithms
    • Fundamentals of probability and statistics
    • Programming (in Python, C++, …)
  • You have affinity with multi-view geometry, 3D projection and 3D processing
  • Affinity with embedded processing is considered a plus
  • Experience with machine learning algorithmic approaches or frameworks (e.g., PyTorch, Tensorflow…) is considered a significant plus
  • You are a team player with good networking and reporting skills.
  • Your English is fluent, both speaking and writing.

How to apply

Applications may be sent by email to and Please include cover letter, CV and contact details of 1 to 3 references. Suitable candidates will be invited for an interview. Application deadline is February 1, 2022, but applications remain welcome until the position is filled. We offer you a flexible starting date, with a preference to start as soon as possible. For more information about the topic of the PhD itself, please contact prof. Luong or dr. Vlaminck.