PDEng position on Predictable Reconfigurable Multi-Source Streaming (V36.3494)

PDEng position on Predictable Reconfigurable Multi-Source Streaming

Aanstellingsfunctie(s)
Technologisch ontwerper in opleiding (PDEng trainee)
Faculteit(en)
Faculteit Electrical Engineering
FTE
1,0
Sluitdatum
11/11/2018
Aanvraagnummer
V36.3494

Functieomschrijving

Electronic systems group at the TU/e
The Electronic Systems (ES) group consists of seven full professors, ten assistant professors, several postdocs, about 30 PDEng and PhD candidates and several technicians 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, Artemis, 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 eight different nationalities and students from all over the world.

Are you ready for a two-year training program while at the same time receiving a salary? Do you like to work in an international, multidisciplinary team of professional experts for the next two years? Would you like to apply your innovative, creative ideas in embedded-systems development in the high-tech healthcare industry? Then you should consider starting as a PDEng trainee at Eindhoven University of Technology, TU/e, www.tue.nl, in the Netherlands and gain a head start on your fellow Master students!

Project description
During the traineeship you follow an individual program, consisting of courses, workshops, professional development and industrial projects, deepening the theoretical knowledge and practical skills gained during your university studies. You will apply all knowledge gained in a large-scale in-company multidisciplinary design project. The project for this traineeship is conducted in collaboration between the Electronic Systems group (www.es.ele.tue.nl) in the Electrical Engineering department of TU/e and Philips Healthcare (https://www.philips.nl/healthcare). You build up a valuable network and can count on professional supervision from both the university and Philips. Your individual training scheme is customized to your personal and professional skills, as well as the demands of the industrial project. 

The envisioned traineeship is part of the recently granted ECSEL project FitOptiVis, coordinated by Philips Healthcare. The objective of FitOptiVis is to develop an integral approach for smart integration of distributed image- and video-processing pipelines for cyber-physical systems (CPS) covering a reference architecture, supported by low-power, high-performance, smart devices, and by methods and tools for combined design-time and run-time multi-objective optimization within system and environment constraints.

In today’s CPS domains such as healthcare, high-tech equipment, and robotics, efficient image and video processing plays a crucial role. The challenge is to ensure low latency, high-performance, and energy efficiency. The trade-off among these conflicting design objectives is key in the design decisions. This calls for a new paradigm of combined model-driven design-time and runtime multi-objective optimization that is specifically targeted for distributed imaging and video-processing pipelines within CPS. 

Predictable reconfigurable multi-source streaming
CPS are complex heterogeneous systems with heterogeneous, partially shared, resources and with dynamic stream data processing applications. Platform virtualization is a method to offer applications their private share of the shared resources without the need to address the interference from other applications sharing the resources. This way, separation of concerns is achieved that dramatically simplifies the development and verification of applications and makes their operation more predictable.

FitOptiVis exploits the virtual platform approach by defining a reference architecture in which system resources are offered to applications as virtual platforms that give applications their dedicated share of system resources with composable functionality and performance. Dynamic reconfiguration of applications and resources is indispensable for an efficient and performant CPS. This requires the possibility to dynamically reconfigure virtual platforms in a composable and predictable manner without disturbing the ongoing operation of applications. 

The PDEng in this position will work closely with PhDs within this research project to (1) prototype a CompSOC based (http://compsoc.eu/) virtual platform which will enable reallocation of resources and applications without compromising the operation and performance of active applications and (2) to demonstrate the technical results in an integrated demonstrator targeting the multi-source streaming FitOptiVis’ use case. The position will be supervised by Dr. Marc Geilen.

Functie-eisen

The vacancy is open to MSc graduates from a top university. You should

  • have an MSc degree in computer engineering or any other relevant program.
  • have theoretical and applied knowledge of embedded programming and software engineering.
  • have experience with FPGA programming.
  • have solid skills in C / C++ programming.
  • have experience with or an interest in signal and/or image processing.
  • have excellent communication skills in English (written and spoken).
  • be a flexible team player, actively helping other team members, and see changes as an opportunity to learn and grow.
  • be a quick learner, able to and interested in acquiring new skills and competences.
  • show a hands-on attitude, taking responsibility for the process from specification to implementation and validation, including communication and alignment with peers.

Arbeidsvoorwaarden

We offer a challenging job in a dynamic and ambitious university through a fixed-term appointment for a period of 2 years. The research must be concluded with the attainment of a PDEng degree. As an employee of the university you will receive a competitive salary as well as excellent employment conditions. The salary is € 1865,- per month (gross). Moreover, an 8% holiday allowance and 8,3% end-of-year allowance is provided annually. Assistance for finding accommodation can be given. The university offers an attractive package of fringe benefits such as excellent technical infrastructure, child care, savings schemes, and excellent sports facilities.

Informatie en sollicitatie

Information

Application

If interested, please use 'apply now'-button at the top of this page. You should upload the following:

  • a detailed curriculum vitae, a letter of motivation and portfolio with relevant work;
  • a cover letter explaining your motivation and suitability for the position;
  • a detailed Curriculum Vitae (including a list of publications and key achievements in research project(s));
  • contact information of two references;
  • copies of diplomas with course grades;
  • results of your IELTS test.

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.

Please keep in mind; you can upload only 5 documents up to 2 MB each.