PhD Scholarship on Error-correction Coding at Eindhoven University of Technology

Eindhoven University of Technology, Netherlands is inviting excellent students to apply for a PhD position in sustainable energy. This position is available for 4 years. There is no application deadline for this position.

The Electronic Systems (ES) group within the Department of Electrical Engineering of Eindhoven University of Technology (TU/e) seeks to hire an outstanding PhD candidate within the field of the implementation of channel coding for next-generation communications systems.

Motivated by Shannon’s channel coding theorem, error-correction coding has become an integral part of all modern communications systems and standards that have enabled the information revolution of the past decades. Recently, there has been a growing interest in mission-critical applications that have extremely stringent reliability and latency constraints, such as autonomous driving, industrial automation, and remote robotic surgeries. The systems used in these applications are referred to as ultra-reliable low-latency communications (URLLC) systems in the context of the newly-introduced 5G communications standard. The most common way to enable ultra-low-latency communications is to use very short data packets that are only, e.g., 64 or 128 bits long. Unfortunately, modern error-correcting codes are typically designed for (and are hence most effective for) long data packets. For this reason, the design of error-correcting codes and corresponding decoding algorithms that specifically target short packets is a research topic that is garnering significant attention.

For example, the short packets that are used in URLLC systems enable the use of novel and exotic decoding algorithms with very strong reliability guarantees that would otherwise be infeasible in terms of their implementation complexity. The efficient hardware implementation of these decoding algorithms as well as their adaptation to specific classes of error-correcting codes is an important open research direction. Moreover, the design of optimal (semi-)random error-correcting codes and decoders using non-linear optimization or machine learning techniques also becomes feasible when using short packets.

The general focus of this project is on the design of error-correction coding schemes, decoding algorithms, and hardware architectures for URLLC systems. The successful candidate for this PhD position will have significant freedom (and will receive the appropriate guidance) to shape the exact research agenda of the project.

Eindhoven (TU/e) is a mid-size technical university located in the heart of the high-tech industry in the Netherlands, named the Brainport region. Eindhoven is the fifth largest city in the Netherlands, and including suburbs it has about 420,000 inhabitants. TU/e is a highly ranked university both in research and education. Our training and research programs are highly regarded and we foster close relationships with companies, organizations and research institutes in the Brainport region and beyond. Fundamental and applied research are equally valued here. The high rank of the TU/e is due to the impact of its scientific research and also to its scientific copublications with industry. TU/e is a social and inspiring university with a fine culture. You will quickly feel at home, surrounded by people who share your scientific ambitions. The TU/e currently has nine departments, with over 11,000 students in total.

The Department of Electrical Engineering teaches highly motivated Masters of Science, designers and doctoral candidates, and carries out breakthrough research in its field. The department has three spearheads: Connected World, Care and Cure, and Smart Sustainable Systems. These themes are reflected in the department nine teaching chairs.

With almost 100 (assistant, associate and full) professors, over 200 PhD and PDEng students, about 800 Bachelor students and 300 Master students, the Department of Electrical Engineering (EE) is one of the largest departments of the TU/e. By performing top-level fundamental and applied research, offering high-quality educational programs, and maintaining strong ties with industry, EE aims to contribute to science and to innovation in and beyond the region. EE currently offers a Bachelor and Master program in Electrical Engineering and participates in several multi-disciplinary masters, such as Systems and Control, Automotive Technology and Sustainable Energy Technology, all taught fully in English. See here for more information about the department.

The department's relationship with the high-tech industry in the Brainport region means that staff and students can contribute directly to the development of technological innovations with real-world relevance. The unique positioning in one of Europe's leading tech regions also means excellent job opportunities for spouses.

The Electronic Systems group is one of the 9 research/teaching chairs within the faculty of Electrical Engineering and consists of seven full professors, ten assistant professors, several postdocs, about 40 PDEng and PhD candidates, and support staff. The ES group is world-renowned for its design automation and embedded signal processing systems research. It is our ambition to provide a scientific basis for design trajectories of electronic systems, ranging from digital circuits to cyber-physical systems. ES research is organized in three subprograms that cover the engineering, system and circuit perspectives: Model-driven engineering, smart electronic systems, and digital nano-electronics. ES has strong collaborations with industry, research institutes and other universities. Thirteen of its staff members have a second affiliation besides their TU/e-ES affiliation. The group is a multi-cultural team, with staff members of eleven different nationalities and students from all over the world.

We offer a fixed-term 4 year challenging position for 4 years in a dynamic and ambitious university and a stimulating research environment.

If interested, please use 'apply now'-button at the top of this page.

Candidates will be selected based on graduation mark and proficiency at university including consideration of the reputation of the university, relevant experience and skills, writing skills and publications, work experience, as well as performance in relevant modeling exercises and interviews.


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