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PhD Position in Computer Vision for 3D Mapping of Transportation Infrastructure

PhD Position in Computer Vision for 3D Mapping of Transportation Infrastructure

Aanstellingsfunctie(s)
Promovendus
FTE
1,0
Sluitdatum
31/08/2020
Aanvraagnummer
V36.4537

Functieomschrijving

The PhD candidate will work within an international ITEA research project SMART in cooperation with industrial partners from Netherlands and Canada. The general goal of the project is to enable safety of all road traffic participants by intelligent transportation systems using a multi-camera network, empowered by computer vision and Deep Learning. The PhD candidate will perform research with potential deployment of results in industrial products of Esri, Sweco, ViNotion and CycloMedia.

The specific objective of the PhD candidate is to research and develop methods for the generation of dynamic 3D models of roads and critical intersections based on the panoramic images already available at CycloMedia. For instance, it is important to detect and map the road lanes, traffic lights, trees, light poles, pedestrian crossings, safety islands, etc. onto the 3D or 2D model of a city map. By inserting actual traffic into the model, it becomes dynamic. The scientific challenge is in developing and training neural network models to understand the input panoramic images and automatically create the 3D/2D local models of intersections. Close cooperation with the company of CycloMedia is envisaged and the research will also be partly integrated into the Dutch national research program on Efficient Deep Learning, offering exciting know-how exchange between PhD students on 3D modelling and AI.

Functie-eisen

The PhD candidate should have a MSc degree in Electrical or Computer Engineering and will be hired as a doctoral student in the Signal Processing Systems/VCA group for a 4-year period. The candidate should have strong background knowledge in image processing and excellent programming skills with some experience in C/C++ and/or the Pytorch environment. The candidate should have background knowledge in image processing, ad experience in working with 3D (or multi-view) geometry. Experience with depth data and point-cloud data processing is highly desired. Knowledge of deep learning algorithms is a prerequisite. Candidates should be fluent in English / academic writing, should have good communication skills and should be able to cooperate in a multidisciplinary team.

Arbeidsvoorwaarden

  • Challenging job in a dynamic and ambitious university and a stimulating internationally renowned research environment;
  • full-time temporary appointment for 4 years;
  • Gross salary between € 2.395,00 and € 2.361,00;
  • Extensive package of fringe benefits (e.g. excellent technical infrastructure, the possibility of child care and excellent sports facilities);

Informatie en sollicitatie

The PhD student will be working in the Video Coding Architecture research group (http://vca.ele.tue.nl ) in the Department of Electrical Engineering at TU/e. The Department of Electrical Engineering is one of the nine departments of the Eindhoven University of Technology and provides BSc and MSc programs in Electrical Engineering. The department has nine large research groups and has research collaborations with other departments at the Eindhoven University of Technology as well as with a large number of other universities and companies, both within The Netherlands and internationally. The Electrical Engineering faculty has approximately 300 employees and 1000 students. 

For more information about the advertised position, please contact:

Prof.ir. Peter H.N. de With (P.H.N.de.With[at]tue.nl )

Dr.ir. Egor Bondarev (e.bondarev[at]tue.nl )

Information

Application

If interested, please use 'apply now'-button at the top of this page. You should upload the following: a detailed curriculum vitae, a letter of motivation and portfolio with relevant work. Please keep in mind; you can upload only 5 documents up to 2 MB each! 

  • Cover letter explaining your motivation and suitability for the position;
  • Detailed Curriculum Vitae (including a list of publications and key achievements in research project(s));
  • Contact information of two references;
  • Copies of diplomas with course grades;