PhD position on Digital Disruption (JADS)

PhD position on Digital Disruption (JADS)

Published Deadline Location
19 Dec 1 Mar Den Bosch
This PhD project will be conducted in collaboration with CZ, one of the four largest health insurance companies in the Netherlands. CZ is one of the forefront runners in understanding how technology will impact the healthcare industry and uses these insights to ensure that the Dutch healthcare remains innovative and of top quality for all citizens and patients. Therefore, the implications of this research specifically for the healthcare context need to be articulated and communicated during the project.

Job description

The research will be conducted under supervision of prof. dr. Arjan van den Born and 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. Knowledge of text mining and natural language processing techniques are a great pre.

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 CZ.

Specifications

Tilburg University

Requirements

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 a strong interest in Text Mining, Prediction Modeling, Complexity Economics, Agent-Based Modelling and Technology Disruption;
  • Have excellent analytical skills;
  • Is highly motivated and rigorous;
  • Have good technical understanding of models used in simulation and statistics;
  • Have knowledge of, or a willingness to familiarize themselves with, current research into new and innovative data science techniques;
  • 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.

Conditions of employment

The PhD student will be employed at Tilburg University.

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  € 2.325,- per month up to a maximum of € 2.972,-., 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).

Employer

JADS

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 iDen Bosch revolves around research, education and valorisation on data entrepreneurship. 

Additional information

Project information

Project background and industry involvement
This PhD project will be conducted in collaboration with CZ, one of the four largest health insurance companies in the Netherlands. CZ is one of the forefront runners in understanding how technology will impact the healthcare industry and uses these insights to ensure that the Dutch healthcare remains innovative and of top quality for all citizens and patients. Therefore, the implications of this research specifically for the healthcare context need to be articulated and communicated during the project.

Empirical exploration of the data-driven ecosystems strategies 
The current age of big data brings new opportunities for business development. Data has already changed multiple traditional industries, such as the music and travel industry. Former incumbents in these industries have been replaced by new data-driven businesses or they have to share the market with these newcomers. Many other industries are in the process of ongoing disruption driven by increasing connectivity and digitization of pretty much everything. To survive, firms have to develop or engage in new data-driven ecosystems, in which related, connected offerings are integrated.

Formally speaking, such an ecosystem represents an alignment structure of the multilateral set of partners that need to interact in order for a focal value proposition to materialize (Adner, 2017). Understanding the nature and dynamics of extant ecosystems in both the target and related industries is therefore particularly important to be able to design and scale up new ecosystems. The power of ecosystem is that it allows to build more customer-centric, integrated and powerful value propositions, while the dangers involve the difficulties in managing the relationships with partners and inherent dependencies upon them.
 
One extreme way for companies to manage such dependencies is to use M&As to acquire a company owning data technologies, algorithms or informative data. Important factors in the evaluation of potential companies to acquire are the possible synergies that the acquirer could capture from these companies and strengthen the ecosystem. 

Therefore, we will answer the following research questions in this part of the project:

  • Which innovation ecosystems can we trace in healthcare and related industries and how do they evolve over time?
  • Which data-driven synergies are inherent in the M&A conducted in travel, fintech and healthcare industries in the last 10 years? Which effects did those M&A have and how did they impact the incumbent firms’ position and the related ecosystem?
  • Which cross-over disruptions from one industry to another can be observed and how do they affect the target industry and its incumbents?
  • Which mechanisms drive these disruptions and how do they differ across various industries and sectors? What are the early signals for the upcoming disruptions?

Simulation of dynamics & disruption 
Starting with simple models of disruption and technology we would like to use simulation techniques in general and Agent-Based Modelling (ABM) techniques specifically to uncover the potential outcomes of technology disruption in terms of market size, market structure, value networks and the winners & losers because of disruption. Here we will start with simple models based on our studies of less complex industries such as travel and media and then translate this to the more complex world of health care. The main research question is:

How can business decision making being improved using simulation & ABM in highly-dynamic contexts where disruption is likely to take place with new technology, new value propositions and new technology as well as influence of rule-setting governments?” 

Specifications

  • PhD
  • Behaviour and society
  • max. 40 hours per week
  • €2325—€2972 per month
  • University graduate
  • 16579

Employer

Location

Sint Janssingel 92, 5211 DA, Den Bosch

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Application procedure

Please contact dr. Ksenia Podoynitsyna in case of further questions regarding this project. When applying, please provide a motivation letter, a detailed CV, proof of English proficiency (TOEFL/IETS). The deadline for submitting your application is March 1, 2020. Starting date of this position is as soon as possible, but preferably between March 1 and September 1, 2020.

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This application process is managed by the employer (Tilburg University). Please contact the employer for questions regarding your application.

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Application procedure

Application procedure

Please contact dr. Ksenia Podoynitsyna in case of further questions regarding this project. When applying, please provide a motivation letter, a detailed CV, proof of English proficiency (TOEFL/IETS). The deadline for submitting your application is March 1, 2020. Starting date of this position is as soon as possible, but preferably between March 1 and September 1, 2020.

Make sure to apply no later than 1 Mar 2020 23:59 (Europe/Amsterdam).