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JADS PhD position on Challenges and added value of streaming data platforms

JADS PhD position on Challenges and added value of streaming data platforms

Instituten en overigen
JADS Den Bosch


Project background and industry involvement

This PhD project will be conducted in collaboration with KPN, a leading telecommunication firm in the Netherlands. Therefore, the practical implications of this research need to be articulated and communicated during the project.

KPN is moving away from a static infrastructure towards a more dynamic infrastructure with streaming data, in which KPN’s Data Services Hub (DSH) will be instrumental. This new set-up of the technological infrastructure has an enormous impact on KPN. Handling large swaths of streaming data does not only require a novel technological infrastructure, but it also has great impact on the organization. First, streaming data typically requires dedicated data mining techniques. Second, streaming data requires different ways of interacting with the customers and employees with more emphasis on shared man and machine decision-making. Third, with streaming data, KPN will add more digital services in their portfolio. This requires new business models to monetize the data. Last, but not least, streaming data typically requires a different way to govern and manage the data. The technical platform should be aligned with KPN’s portfolio of business models and management methods.   

Managing platforms

This project focusses on the soft side of streaming data technologies in general and DSH in particular.
Increasing numbers and connectedness of sensors, devices and software systems is equally mimicked by the increasing interdependencies between the involved individuals and organizations that make up the network. These are imprinted in business models and are shaping business ecosystems. Similar challenges are observed in the internal processes, starting from aligning different teams to data-driven mindset(s) and new business development. 

In this research, we will search for optimal configurations of technology, business models and organizational models, involving the following questions: Which use cases of the DSH are likely to be successful? Which use cases of DSH are likely to have positive (or negative) spill-over effects due to the business and organizational aspects? What are the interdependencies between on-line machine learning algorithms, business models, and organizational models, and how should these be developed and managed? How can we add value to the customers? How should we organize the services on such platforms as DSH accordingly? What skills do we need to be successful and what are the requirements of the organizational culture? 

In this research we will be working with the existing and potential business and use cases of the DSH. These use cases are subdivided into three potential categories; internal use cases, external uses cases and 5G-experiments. In each of these use cases we will study; a) the on-line machine learning algorithms, b) the organizational model and c) the business model in detail. Here we try to uncover the soft and hidden secrets of successes and failures of working with machine learning applied to streaming data. 

The research will be conducted under supervision of dr. Ksenia Podoynitsyna.

Our ideal candidate wants to build the bridges between social sciences on one side, and mathematics, statistics, and computer science on the other side. While a healthy understanding of mathematics & statistics is required in this project, it is more important to have a strong understanding of the various strands of social sciences /entrepreneurship and a capability to translate these theories and ideas to statistical and analytical models. 

The successful candidate is expected to:

  • Perform scientific research in the domain described;
  • Present results at (international) conferences;
  • Publish results in scientific journals;
  • Participate in activities of the group, mainly in 's-Hertogenbosch but also regularly at KPN.


Candidates should:

  • Have a MSc. in Statistics, Data Science, Computer Science, Econometrics, AI or a related discipline, a Research Master, or Management/Entrepreneurship or a similar Social Sciences degree with a significant quantitative component;
  • Have excellent analytical skills; 
  • Have knowledge of, or a willingness to familiarize themselves with, current research into new and innovative data science techniques such as text mining and NLP;
  • Is highly motivated and rigorous;
  • Be a fast learner, autonomous and creative, show dedication and be hard working;
  • Possess good communication skills and be an efficient team worker;
  • Be fluent in English, both spoken and written.


The PhD student will be appointed at JADS via an employment at Eindhoven University of Technology (TU/e) or at Tilburg University (TiU).

We offer:

  • A full-time position.
  • The selected candidate will start with a contract for one year, concluded by an evaluation after approximately 10 months. Upon a positive outcome of the first-year evaluation, the candidate will be offered an employment contract for the remaining three years.
  • A minimum gross salary of  € 2.395,- per month up to a maximum of € 3.061,-. in the fourth year;
  • A holiday allowance of 8% and an end-of-year bonus of 8.3% (annually);
  • Researchers from outside the Netherlands may qualify for a tax-free allowance equal to 30% of their taxable salary (the 30% tax regulation). The University will apply for such an allowance on their behalf;
  • Assistance in finding accommodation (for foreign employees); 
  • The opportunity to perform cutting edge research in a large-scale joint data science project involving TiU, TU/e, JADS and a commercial partner and bringing together expertise of several senior researchers;
  • Support for your personal development and career planning including participation in courses, summer schools, conference visits, research visits to other institutes (both academic and industrial), etc.;
  • A broad package of fringe benefits (including excellent technical infrastructure, savings schemes and excellent sport facilities).

Informatie en sollicitatie

The Jheronimus Academy of Data Science (JADS) constitutes a unique concept in which an integrated approach to Data Science is created by combining the exact sciences of the Eindhoven University of Technology, with the social sciences of Tilburg University. JADS boasts three campuses at Tilburg, Eindhoven and Den Bosch. JADS Campus Den Bosch revolves around research, education and valorisation on data entrepreneurship. 

More information about JADS can be found at   

Do you recognize yourself in this profile and would you like to know more? Please contact dr. Ksenia Podoynitsyna (E: K.S.Podoynitsyna[at] in case of further questions regarding this project.

For information about terms of employment, please contact HR services, hr[at] or +31 40 247 3699


We invite you to submit a complete application by using the 'apply now'-button on this page. The application should include a:

  • Cover letter in which you describe your motivation and qualifications for the position.
  • Curriculum vitae, including a list of your publications and the contact information of three references.
  • Brief description of your MSc thesis.
  • Grades list for both BSc and MSc degrees.
  • A proof of English proficiency (TOEFL/IETS) is very much appreciated.
  • Combine all documents to 1 PDF of maximum 10 MB

If you are interested, we invite you to apply immediately, and not later than September 1, 2020. We plan to have the first interviews in the third week of September 2020.
You can only apply online. 

!!Mind that you will be redirected to the website of Tilburg University. If this is not the case (could happen when you have a registered account on the TU/e website) please go to the vacancy website of TiU. Applications via the TU/e website will not be taken into consideration. 

The starting date of this position is as soon as possible.

About the Jheronimus Academy of Data Science (JADS)

The Jheronimus Academy of Data Science, or ‘JADS’ is a high-level hotspot where researchers, data science students, start-ups, scale-ups and experts of industry collaborate in developing cutting-edge research to real-world solutions. JADS is all about creating added value and impact with its combination of data science and entrepreneurship. JADS constitutes a unique concept in which an integrated approach to Data Science is created by combining the exact sciences of the Eindhoven University of Technology, with the social sciences of Tilburg University. JADS boasts three campuses at Tilburg, Eindhoven and Den Bosch.

The JADS Campus at the Mariënburg convent in Den Bosch revolves around research, education and valorization on data entrepreneurship.We offer:

  • Educational programs at undergraduate, graduate and post-graduate level;
  • Innovative, state-of-the-art research at our three Data Science Centers (Tilburg, Eindhoven, Den  Bosch);
  • A growing ecosystem filled with start-ups, scale-ups, corporates and entrepreneurs;
  • Access to data-driven talent, form a dedicated student who works on the data opportunities of tomorrow to an inspiring professor who can challenge the biggest corporates in their quest for value creation.

Additionally, the Mariënburg Campus, which is the main location of JADS, is located in a historic and beautiful former convent in the heart of the medieval city of ‘s-Hertogenbosch and within walking distance of the central train station.

In short, JADS is a buzzing space where education, research and business meet data science at the center stage.