EngD Admission requirements

Candidates are creative problem solvers and team players who seek interaction - within a multidisciplinary environment - to address problems.

They are eager to learn and are dedicated to the quality and quantity of knowledge gained. They have excellent technical skills. We are looking for candidates with the following profile.

Academic Degree

Candidates possess an academic master degree (MSc) in Mathematics, Statistics, Computer Science, or in a relevant application field of Data Science such as Econometrics and Bio-informatics. The MSc-degree is from an accredited institution comparable to the Eindhoven University of Technology or Tilburg University.

Admission requirements

  • Mathematics & Statistics – a least two semesters of mathematics and statistics. The courses should indicate that the applicant has achieved the mathematical and statistical maturity to be expected of an upper level mathematics / statistics / econometrics graduate.
  • Computer Science – at least two semesters of computer science. Courses on programming, algorithms & data structures, databases, data mining/machine learning are required. Courses on topics such as object oriented programming and web development are recommended. The courses should indicate that the applicant has achieved solid knowledge and experience with the computer science aspects that are highly relevant for Data Science.
  • Data Science – Experience with the application of Data Science technology to real world problems, via projects carried out during their education or their working experience afterwards.


Motivation and eagerness

Candidates show high motivation and eagerness to develop the skills to:

  • Combine generalist thinking and expert thinking in various data domains
  • Formulate opportunities and discover value in data
  • Solve complex problems in a data driven environment.
  • Demonstrate sense for entrepreneurship, business and industrial processes
  • Execute projects in a well-managed, professional way, optimally using resources and obeying constraints
  • Acquire knowledge through a self-directed learning style

Your profile as a candidate

Candidates have an attitude that shows:

  • Technical expertise – desire to become an expert in one or more data domains with a generalist thinking attitude
  • Curiosity – desire to discover, distill, and model a problem down to a clear set of concepts and hypotheses that can be tested
  • Creativity – desire to look at a problem in different ways and find novel solutions
  • Communication skills – desire to communicate effectively with all stakeholders, on all aspects of any data science project that include requirement elicitation, project progress, developed solutions, up to use of data to tell a story.
  • Social skills – desire to collaborate with others, with similar and different backgrounds, to tackle challenging problems


“It is intensely challenging, but you will find your hidden talents and improve yourself. You get the benefits of being a student, learn, get work experience and get paid. It is a really valuable program for the rest of your... Read more
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