PhD position on Mathematical Statistics and Machine Learning Theory

Research / Academic

Current statistical methodology still reflects the use-context of its first development in the 1920s: methods assume that researchers make all important analysis choices before gathering the data. In modern data science age, however, data-driven paradigms have become dominant: many measurements are gathered simultaneously and it is often natural to pursue research questions that were not of obvious interest a priori. Looking at the data is scientifically sensible to do, but the problem is that current statistical methods cannot handle this behaviour well. What is needed for this, is the right mathematical framework, that gives the necessary error control guarantees without all the old restrictive assumptions. In this PhD project you will develop such mathematical foundations by bringing together exciting novel developments in mathematical statistics and machine learning theory, among which: closed testing, bandits, and the new theory of hypothesis testing with e-values, co-developed by your supervisor Dr. Rianne de Heide.

You will:

  • Perform daily PhD-level research
  • Publish results in journals and conference proceedings, and present these at (inter)national workshops and conferences.
  • Contribute to teaching activities related to your work.
  • Be a part of an excellent young research group, and benefit from frequent (virtual) interaction with other internationally renowned research groups working on e-values, such as at CWI (Amsterdam), LUMC (Leiden) and in the US.

We are an inclusive group and diversity is at the heart of our research principles. We care about a good working atmosphere and a good work-life balance. Applications from all groups currently under-represented in academic posts are especially encouraged. We particularly encourage women and people from minority groups to apply.


  • You have, or will shortly acquire a master degree in (applied) mathematics or a related degree with a strong theoretical mathematical component. Enthusiasm for the topic of the project is more important than your choice of specialization in your master’s.
  • You have excellent proficiency in English in speaking and writing (C1; above IELTS 7 or equivalent)..
  • Scientific programming skills are a plus, e.g. in R, Python, C++, Julia, etc.

Salary Benefits:

  • As a PhD candidate at UT, you will be appointed to a full-time position for four years, with a qualifier in the first year, within a very stimulating and exciting scientific environment;
  • The University offers a dynamic ecosystem with enthusiastic colleagues;
  • Your salary and associated conditions are in accordance with the collective labour agreement for Dutch universities (CAO-NU);
  • You will receive a gross monthly salary ranging from € 2.770,- (first year) to € 3.539,- (fourth year);
  • There are excellent benefits including a holiday allowance of 8% of the gross annual salary, an end-of-year bonus of 8.3%, and a solid pension scheme;
  • The flexibility to work partially from home;
  • A minimum of 232 leave hours in case of full-time employment based on a formal workweek of 38 hours. A full-time employment in practice means 40 hours a week, therefore resulting in 96 extra leave hours on an annual basis.
  • Free access to sports facilities on campus
  • A family-friendly institution that offers parental leave (both paid and unpaid);
  • You will have a training programme as part of the Twente Graduate School where you and your supervisors will determine a plan for a suitable education and supervision;
  • We encourage a high degree of responsibility and independence, while collaborating with close colleagues, researchers and other staff.
Work Hours:

40 hours per week


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