Doctoral student (licentiate) in Remote Sensing

KTH Royal Institute of Technology, School of Architecture and Built Environment, Stokholm, Sweden
Deadline: Oct 3, 2019

The overall objective of this research is to develop innovative and robust methods and algorithms that use multitemporal Earth observation (EO) data in general, Sentinel-1 SAR and Sentinel-2 MSI data in particular, for urbanization monitoring in support of sustainable urban development.
The tasks and responsibilities include algorithm development, image processing, classification and change detection, writing reports, scientific articles and licentiate thesis.

Requirements Include:

  • Master’s Degree in Geomatics, Electrical Engineering, Computer Science, or other natural sciences and engineering disciplines.
  • Good knowledge in image processing, pattern recognition, machine learning/deep learning.
  • Demonstrated programming skills to implement relevant Java and / or C ++ methods and techniques.
  • Ability to design, implement and test algorithms for processing and classifying satellite images.

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