University of Technology (TU/e, https://www.tue.nl/en/) is one of Europe’s top technological universities, situated at the heart of a most innovative high-tech region, with a wealth of collaborations with industry and academic institutes. Since 2009, the TU/e is Europe’s best-performing university in terms of research cooperation with industry (according to CWTS Leiden Ranking). TU/e has around 3,000 employees and 2,300 PhD students (half of which international, representing about 70 nationalities).
The envisioned research is part of the recently granted ECSEL Joint Technology Undertaking (JTU) project TRANSACT, coordinated by Philips. The goal of TRANSACT is to develop a universal distributed solution architecture for the transformation of safety-critical cyber-physical systems from local, stand-alone systems into safe and secure distributed solutions.
To that end TRANSACT will leverage edge and cloud eco-systems to lower CPS’ cost, increase their pace of updates, and improve applications and solution-oriented services.
The Electronic Systems group of the Electrical Engineering department at TU/e calls for applications for three PhD positions and one Postdoctoral position funded in the TRANSACT project. The focus of the work will be on model-based approaches to analyze and manage timing performance in distributed edge/cloud platforms for safety-critical applications.
PhD position 1: Model inference
Model-based methods based on mathematical application models such as scenario-aware dataflow models provide powerful performance analysis and automated management techniques. The TRANSACT project copes with industrial distributed cyber-physical systems for which such models are not readily available. The goal of this project is therefore to infer stochastic models from the logging data obtained from the CPS. These models will be used as a basis in the other PhD projects to develop performance analysis and performance management techniques. The focus will be on concurrent models such as scenario-aware dataflow models, message sequence charts or activity models This project will i) identify the required models-of-computations (MoCs) based on industrial use-cases, ii) formalize them with respect to syntax and semantics, and iii) develop automated inference techniques (possibly based on Machine Learning) to obtain model instances in the different MoCs.
The position is supervised by prof.dr.ir. Jeroen Voeten and dr. Mitra Nasri.
PhD position 2: Performance analysis
This project concerns the development of performance-analysis techniques, based on the concurrent models obtained in PhD position 1. Focus will be on timing properties and resource usage, for trend and anomaly detection, root-cause analysis, what-if analysis and design-space exploration. We consider safety-critical applications, which may have to deal with significant timing variations, due to the heterogenous distributed nature of the edge/cloud platform. To deal with these timing variations, we will develop techniques that combine worst-case analysis with stochastic analysis. Computationally tractable variants of these techniques will form the basis of the online performance management techniques of PhD position 3.
The position is supervised by dr.ir. Marc Geilen, prof.dr.ir. Jeroen Voeten and prof.dr.ir. Twan Basten.
PhD position 3: Performance management
This project deals with online performance management techniques that prevent the CPS from violating safety or performance requirements. Systems are characterized with models inferred with techniques developed in PhD position 1. The management techniques involve online performance monitoring and prediction techniques (based on the work of PhD position 2), fallback scenario’s replacing high quality, but less certain operations (e.g., high-resolution imaging algorithms deployed in the cloud) by guaranteed but lower-quality services (e.g., low-resolution counterparts deployed in the edge), and techniques to re-deploy applications when resources are congested. The management techniques should ensure predictable and reliable quality of service amidst diverse and partially unreliable resources.
The position is supervised by dr.ir. Marc Geilen, prof.dr.ir. Twan Basten and dr. Mitra Nasri.
Postdoc position: integral role
The postdoc in this project will have an integral role and will actively collaborate with the three PhD candidates listed above and with external project partners. Goal of this postdoctoral project is to develop a method to guarantee safety and performance in distributed edge/cloud platforms for safety-critical CPS, based on the model inference, performance analysis and performance management techniques developed in the PhD projects. This includes the demonstration and validation of the method on the TRANSACT use cases.
We are looking for highly motivated candidates with very good English proficiency.
PhD candidates need to have obtained a relevant master’s degree (Computer Engineering, Informatics or Computer Science, Electrical Engineering - ideally with a focus on Cyber Physical Systems) with excellent grades. Postdoc candidates must have a relevant PhD degree and excellent communicative skills. Candidates must have strong analytical skills, affinity for formal models and semantics, algorithmic solutions, as well as software engineering practices and good programming skills.
Specific for a PhD position:
Specific for a Postdoc position:
Do you recognize yourself in this profile and would you like to know more? For more information about the advertised positions, please contact:
Prof. dr. ir. Jeroen Voeten, j.p.m.voeten[at]tue.nl
Dr. ir. Marc Geilen, m.c.w.geilen[at]tue.nl
Prof.dr.ir. Twan Basten, a.a.basten[at]tue.nl
Dr. Mitra Nasri, m.nasri[at]tue.nl
Ir. Víctor Sánchez, v.sanchez.martin[at]tue.nl
For information concerning employment conditions click here.
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 'apply now'-button on this page.
The application should at least include the following information (only pdf files are accepted):
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.
Electronic systems group at the TU/e
The Electronic Systems (ES) group consists of five full professors, two associate professor, six assistant professors, several postdocs, about 30 PDEng and PhD candidates and support staff. The ES group is world-renowned for its design automation and embedded 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. The group is strongly involved in the electrical engineering bachelor and master programs of the TU/e, as well as in the automotive bachelor program and the embedded systems master program. The group has excellent infrastructure that includes individual computers, computer servers, state-of-the-art 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. Eleven of its staff members have a second affiliation besides their TUE-ES affiliation. The ES group has been very successful in attracting funding for its research through national and international projects and collaborations (EU programs: H2020, ITEA, CATRENE, ECSEL, PENTA, Marie Curie; national programs: NWO, RVO, contract research), for a total budget of around 2M euro per year. The ES group is a multicultural team, with staff members of five different nationalities and students from all over the world.