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  3. PhD position in the SmartOne KPN-TU/e Flagship in the DLCE project

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PhD position in the SmartOne KPN-TU/e Flagship in the DLCE project

In the context of the joint research project between TU Eindhoven and KPN we have one 4-year PhD student position in the Data Mining group at the Department of Computer Science, TU/e Eindhoven.

12 maanden geleden


de Rondom, Eindhoven, Noord-Brabant
Tijdelijk contract / Tijdelijke opdracht
Uren per week:
38 uur


Development of intelligent applications running advanced machine learning models on the edge of the network such as mobile, smart home, internet-of-things platforms require connectivity and computing resources. As the complexity of the applications grow (i.e. streaming video processing, virtual/augmented reality, mobile solutions) the computer network infrastructure between the point of service and the compute infrastructure is becoming a bottleneck. With the advancements of hardware at the edge of the network, where the actual service is needed, the possibility to move some or most of the computational load is becoming evident.

Thus, we aim to study methods for extending deep neural network models from the core of the network into models that exist both on the edge and on the core. The main practical goal is formulated as: taking into account network factors such as available resource on the edge, connectivity, bandwidth, latency and jitter, provide reliable, efficient and scalable Deep Learning based solutions to a multitude of connected devices. To achieve this goal, we will study the issues of DLCE reliability, efficiency, scalability and improved experience.

This project is in collaboration with KPN, a Dutch landline and mobile telecommunications company. DLCE is part of a larger project TU/e-KPN flagship SmartONE, which constitutes an interdisciplinary collaboration between KPN and 4 TU/e research centers: Smart Cities, Wireless Technology, Photonics Institute and Data Science.


We are looking for candidates that meet the following requirements:

  • a solid background in Computer Science with specialization in deep learning, machine learning, data mining or related areas (demonstrated by a relevant Master project);
  • have a strong interest in deep learning research;
  • have machine learning/data mining software development skills at least in one language, e.g. R, Python, Java; familiarity with deep learning libraries and Python is a plus.
  • good communication skills in English, both in speaking and in writing (candidates from non-Dutch or non-English speaking countries should be prepared to prove their English language skills);
  • capability and willingness to work both independently and in a team of data scientists and interact with domain experts; being highly motivated, rigorous, and disciplined.

  • PhD students are expected to:
  • perform scientific research in the domain described
  • collaborate with other researchers in this project, transfer knowledge to internal specialists at KPN and assist in guiding (project-related) MSc thesis projects
  • participate in doctoral training on relevant topics
  • present results at leading international conferences in the field
  • publish results in scientific journals
  • be willing to work at two locations (TU/e campus in Eindhoven and KPN office in [Amsterdam/The Hague)

  • Arbeidsvoorwaarden

    We offer:
  • A full time temporary appointment for a period of 4 years, with an intermediate evaluation after 9 months;
  • A gross salary of €2.222 per month in the first year increasing up to €2.840 in the fourth year;
  • Tight collaboration of academia with industry with access to real data and domain expertise.
  • Strong collaboration ties with several research groups in Europe and world-wide.
  • Healthy travel funding for presenting your work at the leading conferences and for visiting research.
  • Support for your personal development and career planning including courses, summer schools, conference visits etc.;
  • A broad package of fringe benefits, e.g. excellent technical infrastructure, child daycare and excellent sports facilities, extra holiday allowance (8%, May), and end-of-year bonus (8.3%, December).
  • Additionele informatie

    More information:
  • For more information about the DLCE project contact dr. Vlado Menkovski v.menkovski@tue.nl and prof. dr. Mykola Pechenizkiy m.pechenizkiy@tue.nl.
  • For more information about the employment conditions contact Arianne Boekema (HR advisor), e-mail: pzwin@tue.nl or by telephone: +31 40 247 2321.

  • Application:

    The application should consist of the following parts:
  • Cover letter explaining your motivation and qualifications for the position;
  • Detailed Curriculum Vitae;
  • List of courses taken at the Bachelor and Master level including grades;
  • A copy or a link to your MSc thesis. If you have not completed it yet, please explain your current situation.
  • List of publications (with links to download) and/or software developed (links to GitHub);
  • Names of at least two contacts who can be approached with a reference letter request.

  • Selected candidates with be invited first for a Skype interview and then for onsite visits to TU/e and KPN.

    The selection process with start in March 2018 and will continue until the positions get filled. The position is fully funded and immediately available. The start date is flexible. The successful candidates are expected to start before summer 2018.

    Please apply by using the 'Apply now' button on top of this page. Applications submitted by e-mail will not be considered.