Munich Aerospace awards 16 PhD scholarships

Munich Aerospace awards doctoral scholarships in the field of aerospace research to support young scientists. The scholarships are aimed at qualified university graduates who have completed their studies in a field relevant to aerospace and are now aspiring for a doctorate at the Technical University of Munich or the Bundeswehr University Munich.

Further information on the PhD topics can be found in the PDF files below:

General information on PhD scholarship conditions can be found here. Abstracts of the newly acknowledged Munich Aerospace research groups can be found here.

Scholarship applications expired:

  • – Agri-food Supply Monitoring from Earth Observation Data (Industry cooperation with IABG, Lead: Prof. Xiaoxiang Zhu)
  • – Adaptive Few-shot Change Detection for Earth Observation (Industry cooperation with IABG, Lead: Prof. Xiaoxiang Zhu)
  • – Analysis and Development of AI-based Concepts for Ground Based Collision Avoidance in Single- and Multi-Satellite-Systems (Lead: Prof. Roger Förstner)
  • – Intelligent fault-tolerant flight guidance (Lead: Dr. Gertjan Looye)
  • – Development of AI-based on-board guidance & navigation procedures for the safe and optimal execution of avoidance manoeuvres in the context of autonomous collision avoidance in multi-spacecraft systems (Lead: Prof. Roger Förstner)
  • – Lightweight Code-based Quantum-Resistant Cryptography. The activity aims at developing lightweight quantum-secure crytosystems for hardware-constrained satellite loT terminals (Lead: Prof. Gerhard Kramer)
  • – Certifiable Control Allocation for eVTOL (Lead: Dr. Gertjan Looye)
  • – Hybrid lightweight structures by using of additive manufacturing (Lead: Prof. Eric Jägle)
  • – Hybrid lightweight structures by additive manufacturing (Lead: Prof. Eric Jägle)
  • – Experimental Analysis of Drop-In Biofuels as an Alternative Fuel for Small Aero Engines (Lead: Dr. Christian Helcig)
  • – Performance and Emissions of Helicopter Engines using Drop-In Biofuels (Lead: Dr. Christian Helcig)
  • – Efficient structure exploitation on GPUs for discretized optimal control problems (Lead: Prof. Matthias Gerdts)
  • – Robust Model Predictive Control under Uncertainties (Lead: Prof. Matthias Gerdts)

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