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TUD Dresden University of Technology, as a University of Excellence, is one of the leading and most dynamic research institutions in the country. TUD has established the Research Training Group "AirMetro – Technological & Operational Integration of Highly Automated Air Transport in Urban Areas" (RTG 2947)1, funded by the German Research Foundation (DFG). This interdisciplinary group, involving five faculties and the German Aerospace Centre (DLR), will conduct research on 11 research topics with 22 PhD candidates in the first funding period (05/2024 to 04/2029). The goal is to address the technical and social challenges of Advanced Air Mobility, considering ecological, economic, technological, and sociological factors. The RTG's structured doctoral program aims to train young researchers in highly automated, networked mobility, featuring international collaboration with mentors from the USA, Asia, and Europe. TUD and the RTG embodies a university culture that is characterized by cosmopolitanism, mutual appreciation, thriving innovation and active participation. For TUD diversity is an essential feature and a quality criterion of an excellent university. Accordingly, we welcome all applicants who would like to commit themselves, their achievements and productivity to the success of the whole institution.
The Research Training Group RTG 2947 "AirMetro", funded by the DFG, offers a position as
Research Associate / PhD Student (m/f/x)
(subject to personal qualifications, employees are remunerated according to salary group E 13 TV-L)
starting as soon as possible. The position is limited to 48 months, max. until April 30, 2029. The period of employment is governed by the Fixed Term Research Contracts Act (Wissenschaftszeitvertragsgesetz – WissZeitVG). The position aims at obtaining further academic qualification (usually PhD).
Job ID: RTG2947-T6
Title: Development of Robust Motion trajectories under Consideration of Model and Data Uncertainty
Investigators: Prof. Michael Kaliske, Chair of the Institute for Structural Analysis and co-supervised by at least one additional professor plus an international tutor of the RTG
Requirements: very good university degree as Master of Science (M.Sc.) or Diplom-Ingenieur (Dipl.-Ing.) in civil engineering or mechanical engineering (or comparable) with deep knowledge in uncertainty quantification, structural analysis, advanced mathematics, modelling and simulation.
Description of the PhD topic: Small, highly automated aircrafts over populated areas rely on robust motion trajectories, considering uncertain input data. Sensor precision, fusion of multiple data sources and absence data due to difficult environmental conditions or technical defects require the modelling of vehicle states beyond deterministic models. The objective of this PhD thesis is to develop and apply appropriate polymorphic uncertainty models in order to continuously determine robust motion trajectories. The project aims to overcome drawbacks of probabilistic models by means of problem adapted data modelling and the application to realistic data scenarios.
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