Eindhoven University of Technology (TU/e) is one of Europe's leading research universities.
The Eindhoven area, in the southern part of the Netherlands, is one of Europe's top innovation ecosystems, with many high-tech companies and institutes, such as Philips, ASML, NXP, DAF, OCE, and the Holst Centre. TU/e is closely intertwined with many of these companies and institutes, and research at TU/e is characterized by a combination of academic excellence and industrial relevance. Culturally the Netherlands is a very interesting part of Europe. Historic cities such as Amsterdam, The Hague, Maastricht, Brussels, and Antwerp are all within easy reach from Eindhoven.
Within the Electrical Engineering department of TU/e, the signal processing systems group is broadly concerned with signal and information processing theories, algorithms, architectures and systems. The group uses challenging application vehicles to drive the development of its fundamental expertise. These vehicles are selected in close collaboration with strategic partners in the regional innovation ecosystem, in areas such as personal healthcare, smart surveillance, self-driving cars, wireless and fiber-optical communication, and intelligent lighting. A thorough understanding of such applications permits key application features to be captured in mathematical models, as a basis for model-based signal and information processing techniques which are inherently more powerful than classical 'black box' techniques. This model-based approach permits the group to combine academic excellence with a strong real-world impact, visible in many strong industrial and clinical collaborations and in 9 spin-off companies.
The group has a collaborative, entrepreneurial, and informal working atmosphere, with
13 full-time scientific staff members, 9 senior clinical and industrial experts who are appointed as part-time professor, and around 70 PhD students and postdocs. Its strong international scientific reputation is evidenced by e.g. 7 Fellowships of IEEE, AES and OSA.
To reinforce this vibrant community we are looking for a new tenure-track scientific staff member.The vacancy:
Exponential advances in microelectronics, digital communication and data storage are ushering in the information age. In the years ahead, virtually any technological product will produce massive information streams via embedded sensors and logging devices, as a basis for various forms of intelligence. For example, cars will become massive sensor platforms with cameras, radars, ultrasound sensors, LIDAR, and GPS tracking, jointly used for accurate real-time environmental perception so as to enable autonomous driving. Similarly, the emerging internet of things will evolve into a massive distributed sensor cloud that adds a broad layer of intelligent support to our lives. As a third example, future 5G wireless systems will employ massive antenna arrays to provide dependable high-speed data links to many mobile terminals simultaneously. In all these cases, massive and often distributed streams of signals need to be produced, processed and interpreted to provide reliable information in the face of probabilistic and often nonstationary interferences, artifacts, and noise.
Because of the exponential advances in microelectronics, it becomes increasingly feasible to implement information-processing algorithms that closely approach fundamental performance limits. A well-known fundamental limit is Shannon's capacity limit for single-user communication channels. It took fifty years of efforts and inventions, but now there exist advanced coding techniques that closely approach this limit with the technologies that are available today. For new information processing scenarios, there is a similar need to identify fundamental limits and to design efficient processing schemes that approach them. To this end, in-depth knowledge of information theory and probabilistic signal-processing theory needs to be coupled to detailed insights on and mathematical models of the processing scenario.
This vacancy is embedded in the Information and Communications Theory Lab (ICT Lab), where information processing is studied in a broad sense. The Lab focuses on finding fundamental limits but also on the data processing techniques (often codes) and architectures that approach these limits. Information-theoretical frameworks are typically used to model the scenarios under investigation, which follow from result from close interaction with industry. Current areas of interest in the ICT Lab include source coding, channel coding, modulation, multi-user information theory, fiber optical communications, and security.
We are looking for a new scientific staff member to reinforce our expertise, in close collaboration with existing staff members and strategic partners in the innovation ecosystem. Potential topics of specialization include, but are not limited to,
- Future wireless communication systems,
- Source coding and error control coding,
- Information-theoretic security,
- Digital signal processing and digital communications,
- Visible light communications,
- Quantum information theory,
- Machine learning and its applications, and
- Sensing and positioning including radars.
The candidate pursues top-level research in the broad field of communication and information theory. The research combines academic excellence with real-world relevance, with due account for issues such as algorithmic efficiency, elegance, and robustness. The candidate actively collaborates with other staff members and with strategic partners in the innovation ecosystem, and contributes to the acquisition of funds for these projects. He/she coaches graduate, post-graduate and PhD students, and contributes to the educational activities of the group at undergraduate and graduate level.