Phd in Artificial Intelligence and Marketing

Amsterdam Business School – Operations Management Section

14 maart 2018
€2,222 to €2,840 gross per month
1 mei 2018
38 hours per week

The Amsterdam Business School (ABS) is a partner of Amsterdam Data Science, a network consisting of the academic knowledge institutes in the Amsterdam Metropolitan Area, and worldwide industry partners that focus on stimulating research and education in Data Science. The ABS is part of the Faculty of Economics and Business (FEB). The FEB provides academic programmes for more than 5,500 students and employs about 400 people. The Faculty conducts research in many specialist areas and participates in the Tinbergen Institute, one of Europe's leading graduate schools in economics, finance and econometrics.

Project and job description

The Operations Management section of the Amsterdam Business School is looking for a PhD candidate for an interdisciplinary project in the fields of computer science and marketing.

Topic: The decision for the location of a retail store has been of key importance to companies as it is well known that location is a prime factor for retail patronage decisions and a strong source of competitive advantage. In this project, we take advantage of the neighbourhood-level open data statistics, as well as social multimedia (e.g. user-generated images, text and various metadata) and other channels to research the problem of store location, store popularity and store design. Specifically, given a set of potential areas in a city to open a store, our aim is to identify the most promising ones in terms of store popularity. In addition, we aim at identifying the ‘look and feel’ that will create store popularity.

The PhD candidate will work on:

  • developing a store placement model based on social multimedia and open data;
  • testing the model transferability and scalability to the other cities in The Netherlands;
  • extending the model to the cities abroad, with completely different data availability and cultural context;
  • investigating the models for quantifying reliability of data sources and models;
  • proposing efficient and effective evaluation protocols, involving emerging technologies such as crowdsourcing.


  • Master’s degree in Computer Science, Artificial Intelligence, Econometrics (with a strong affinity towards CS/AI) or related field;
  • experience with computer vision, information retrieval and machine learning;
  • excellent programming skills in, for example, Python, C++ or Java;
  • solid mathematics foundations, especially statistics and linear algebra;
  • motivation to publish in top-level academic journals in computer science and marketing;
  • fluent in English, both written and spoken.

Further information

For further information, please contact:


The appointment will be for a period of 4 years, with an intermediate evaluation after 18 months.  End-result should be a PhD thesis. An educational plan will be drafted that includes attendance of courses and (international) conferences. The PhD candidate is also expected to assist in teaching at undergraduate level.

The gross monthly salary will range from €2,222 in the first year to €2,840 in the last year. The Collective Labour Agreement (CAO) for Dutch Universities is applicable.

What do we offer you?

Some of the things w.e have to offer:

  • a unique community of Data Science researchers;
  • a friendly and informal working environment;
  • high-level of interaction;
  • location in the city centre;
  • international environment;
  • access to high-end computing facilities.

Amsterdam is a very international city where almost everybody speaks and understands English.

Job application

You may apply via Please quote vacancy number 18-118 in the subject line.

All applications should include a:

  • curriculum vitae;
  • list of university courses taken with grades;
  • single page maximum statement of motivation and research interests. 

An interview and a scientific presentation will be part of the selection process. #LI-DNP

No agencies please

Gepubliceerd door  Universiteit van Amsterdam