You will develop a mathematical framework for multiple testing, enabling flexibility in study design, analysis, and model choice while retaining strong error guarantees. This means that researchers can adapt their research questions and sampling plans to the data as they come in and in a way that is as model-free as possible. We achieve this by combining three recent exciting novel developments in mathematical statistics. The new theory of hypothesis testing with e-values, co-developed by Dr. Rianne de Heide, allows for flexible sampling plans. Prof. Jelle Goeman co-developed the closed testing framework that gives flexibility for defining research questions in a data-dependent way. Thirdly, we add permutation- and knockoff-based methods that allow for relatively model-free inference. In this project, we aim to combine the strengths of these three frameworks into a novel and coherent whole.

The project is funded by an M2 grant from NWO (the Dutch research council), and is a collaboration between the University of Twente (UT) and the Leiden University Medical Centre (LUMC). The grant funds two PhD students and a scientific programmer. You will be supervised by both Rianne de Heide and Jelle Goeman. One PhD student will be appointed at the UT, and one PhD student at the LUMC. We collaborate very closely, e.g. have group meetings, together with the PhD students who are already working on these topics and are co-supervised by Goeman and De Heide. If you apply to this vacancy, you can indicate you preference for getting appointed at the UT or at the LUMC. Therefore, you can also apply here if you have a preference for working at the LUMC.

We will review applications on a rolling horizon. As soon as we find a suitable candidate, we will arrange an interview. If it turns out to be a match from both sides, we will hire the candidate either at the UT or the LUMC (you can indicate your preference). We will close the vacancy as soon as these two positions are filled.

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.