The project focuses on designing analyzable machine-learning (ML) based scheduling - for real-time systems (in automotive, high-tech systems, and health application areas). This project is distinct from existing learning-based scheduling solutions in that the focus is on providing adaptive ML-based scheduling solutions that can be “analyzed” and “explained” in order to be applicable in safety-critical real-time systems, where the end-to-end worst-case response times (WCRT) of the system must be guaranteed to ensure the system’s safety. To achieve this objective, the project follows two steps:
(1) designing scalable and accurate “analysis techniques and tools” to derive WCRT of a learning-based scheduler. The goal is to define effective system abstractions that allow performing a scalable yet accurate reachability analysis on the space of all possible system behaviors that could be observed under the proposed smart scheduler.
(2) designing efficient smart scheduling solutions that are explainable and can be analyzed by the framework provided in the first step.
The candidate has excellent mathematical and computer science and engineering skills and has affinity with machine learning and scheduling. The candidate is highly motivated and eager to learn new topics and can acquire the knowledge she/he needs very fast to be able to achieve good results in this project.
This project targets a challenging yet very hot topic in safety-critical systems and hence provides ample opportunities for the candidate to accomplish impactful scientific results that are highly visible. If you like to take this challenge and you think you have the right skills, then you may just be the candidate that we are looking for.
Eindhoven University of Technology (TU/e, https://www.tue.nl/en/) is one of Europe's top technological universities, situated at 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 at TU/e. The high rank of the TU/e is due to the impact of its scientific research, and also due to its scientific co-publications 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 12,000 students in total.
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 Embedded Systems, all taught fully in English.
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 nine groups within the department of Electrical Engineering and consists of about 20 scientific and support staff, several postdocs, an about
40 PDEng and PhD candidates. The ES group is world-renowned for its design automation and embedded systems research. The ambition is 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. The group has an excellent lab infrastructure that includes individual computers, computing servers, FPGA and GPU farms, sensor and ad-hoc networking equipment, a cyber-physical systems lab, an electronics lab, and a comprehensive range of electronic-design software. ES has strong collaborations with industry, research institutes and other universities. The group is a multi-cultural team, with staff members and students from all over the world.
We are looking for candidates that match the following profile:
Do you recognize yourself in this profile and would you like to know more?
Please contact dr. Mitra Nasri (m.nasri[at]tue.nl) or prof.dr. Jeroen Voeten (j.p.m.voeten[at]tue.nl) for more information about the advertised position and any informal enquiries.
For information about terms of employment, click here or contact Linda van den Boomen,
HR Advisor, l.j.c.v.d.boomen[at]tue.nl
Please visit www.tue.nl/jobs to find out more about working at TU/e!
We invite you to submit a complete application by using the 'solliciteer nu'-button on this page.
The application should include a:
Candidates will be selected based on grades and proficiency at university including consideration of the reputation of the university, relevant experience and skills, writing skills and publications, work experience, spoken English and presentation skills, as well as performance in relevant modeling exercises and interviews.
We look forward to your application and will screen it as soon as we have received it.
Screening will continue until the position has been filled.
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