2 Research positions in Data Science


PhD in Data Science

We have two vacant PhD positions in the area of data science and machine learning. The goal is to investigate and develop new machine learning techniques that can assist people in certain tasks; in the first PhD project the goal is to learn preferences of planners and drivers to improve vehicle routing, and in the second PhD project, the objective is to investigate explainable machine learning methods for risk estimation of transactions.

The research is performed as part of an R&D project with a company. You will investigate broadly applicable machine learning techniques that can address the problems of the company, among others. You will be given access to their real-life data and discuss ideas and results with them.

In more detail for the first project, the goal is to investigate preference learning techniques for the planning and routing of deliveries of cooled trucks. Existing vehicle routing methods are too rigid in a complex environment such as congestion-heavy cities, especially when taking sustainability aspects like fuel consumption, emissions and driver preferences into account. Automatically learning preferences and best-practices can lead to smarter and more human-friendly planning systems.

The second project's goal is to investigate explainable machine learning techniques for risk estimation, including fraud detection. Machine learning and fraud detection techniques can automate easy cases of risk estimation, but the responsibility remains with the operators. Explainable machine learning has the potential to create a hybrid environment which learns from historic data and provides feedback and recommendations to the operators.

Your task

You will read literature, discuss ideas, develop algorithms and prototypes, publish papers and participate in international conferences. You will join an enthousiastic and open-minded team of researchers in a flexible and rewarding work environment.

The research will be carried under the supervision of Prof. Tias Guns at the Data Analytics Lab of the Vrije Universiteit Brussels, VUB in Belgium:

The Data Analytics Laboratory is a vibrant research team of data scientists which actively engage in research projects with the industry for developing innovative business applications of Big Data Analytics.

For more information or questions, contact Tias Guns: or +32 (0) 2 629 24 11.


  • The candidate has an academic Master degree;
  • Programming experience, for example in Python, R or another language;
  • Having a good knowledge of English;
  • Having an appetite for data science and for working with other people is a plus. Machine learning or optimisation experience is a plus too.

The candidate is expected to endorse the educational vision of the university (full text available on the university website).

Female candidates are particularly encouraged to apply.


As an employee of the Vrije Universiteit Brussel your days will be spent in a dynamic, diverse and multilingual environment. Both our campuses are set within green oases on the outskirts of the centre of the capital of Flanders, Belgium and Europe. This centre, with all its opportunities, is within your reach by public transport in under half an hour.

Depending on your experience and academic merits you will receive a salary on one of the pay scales laid down by the government. Hospitalisation cover and free use of public transport for travel to and from work are standard conditions of employment. If you would rather cycle to work, compensation is also available for that. Both campuses have extensive sporting facilities which are at your disposal and a nursery is within walking distance.

More information is available at under the heading ‘future employees’.

  • Planned starting date: 01/03/2018 or later
  • Length of contract: 1 year, extendable to 4 years upon positive evaluation
  • Deadline for application: 31/01/2018

Applications can only be submitted online (via the website of the Vrije Universiteit Brussel).

Applications should include:

  • a CV
  • a concise motivation letter
  • a copy or picture of your diploma