About 22 hours - Technische Universiteit Eindhoven - Eindhoven
numerically-oriented PhD student position in Unraveling the effect of microstructure statistics on failure of multi-phase steels.(UNFAIL) A PhD vacancy is av…
Eindhoven University of Technology (TU/e) is one of Europe's top technological universities, situated in the heart of one of Europe's largest high-tech …
Eindhoven University of Technology (TU/e) is one of Europe's top technological universities, situated in the heart of one of Europe's largest high-tech innovation ecosystems. Research at TU/e is characterized by a combination of academic excellence and a strong real-world impact. This impact is often obtained via close collaboration with high-tech industries.
The ambition of the PRYSTINE project is to strengthen and to extend traditional core competencies of the European industry, research and universities in smart mobility and in particular the electronic component and systems and cyber-physical systems domains. PRYSTINE's target is to realize Fail-operational Urban Surround perceptION (FUSION) which is based on robust Radar and LiDAR sensor fusion and control functions in order to enable safe automated driving in urban and rural environments. PRYSTINE's consortium, is composed of 60 project partners from 14 different European and non-European countries, including leading automotive OEMs, semiconductor companies, technology partners, and research institutes. PRYSTINE will deliver a fail-operational sensor-fusion framework on component level, dependable embedded E/E architectures, and safety compliant integration of Artificial Intelligence (AI) approaches for object recognition, scene understanding, and decision making within automotive applications. The resulting reference FUSION hardware/software architectures and reliable components for autonomous systems will be validated in in 22 industrial demonstrators.
Within the PRYSTINE project TU/e will focus on enhanced passive/active imaging (cameras-radar-lidar). More specifically TU/e will provide a pool of radar/vision fusion architectures and interpretation algorithms for object recognition and classification, scenario assessment, motion estimation and decision making. Moreover TU/e will implement the developed sensor fusion algorithms onto the computing hardware. The advertised PhD position is situated in the Information and Communication Theory Lab in which expertise in radar technology is available.
We are looking for candidates who
- have a strong MSc degree in signal processing for communications, information theory, or a related discipline;
- can bridge the distance between advanced fundamental concepts and theories on the one hand and practical implementation and evaluation of these concepts on the other hand;
- can think out of the box, distinguish main lines from details, and provide structure to their work;
- have excellent multidisciplinary team working and communication skills.