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Qualification

The qualification program consists of:

  •  RTG specific lectures given by the members of the RTG
  • The "Experimentierstube" 
  • Lectures with external guests from industry and science
  • Tutorials by the Mercator-Fellow and visiting scientists as well as summer schools
  • Softs skills (in colaboration with the Graduiertenakademie)

RTG specific lectures

The following advanced courses are proposed:

  • Simultaneous Localisation and Mapping, Concepts for integrity, Image analysis, Realtime systems, Kinematic multi-sensorsystems, Structure from motion, scientific working
  • Robust and efficient filterung, robust parameter estimation and fuzzy-theory, decision theory and riskanalysis with uncertainties, car navigation, geosensor networks, relational and nonSQL databases

Jour Fixe

Weekly meetings of the PhD candidates

  • Presentations by the candidates (Training in presenting)
  • Reading Club (Discussions vof basic papers)
  • Paper Garage (Scientific writing)
  • Supervisors' day

Experimentierstube

The  Experimentierstube is an open research laboratory, where all PhD candidates of the RTG can test and validate their individual research in cooperation with their collegues. This laboratory is the basic infrastructure to measure real data and make dedicated experiments. The workflow and specific tasks are organised and carried out by the PhD candidates; Postdocs and associated members also contributes.

In order to get quickly familiar with this laboratory, the modul "Experimentierstube" is proposed and must be successfully be completes by the candidates. The modul is subdivided in nine topics consisting theoretical concepts of experimental planning and validation as well as practical excerses with different sensors and analyes tools. Team working and networking are additional objectives of this module.

During the project, together the PhD candidates will carry out dedicated measurement campaigns and data analyses sessions („Mapathons“). Here multiple platforms will be instrumented and operated simulaneous in real environment; thus, forming a collaborative and dynamic sensor network.