Serte Donderwinkel

I am an assistant professor (with a tenure track) in probability theory at the University of Groningen. I am also affiliated with the interdisciplinary centre CogniGron of mathematicians, statisticians, computer scientists and material engineers that aim to improve learning-based cognitive computing with materials-centred systems. 

 Before that, I was a postdoctoral researcher at McGill University in the research group of Prof. Louigi Addario-Berry, where I was funded by a CRM-ISM Postdoctoral Fellowship. I completed my PhD at the University of Oxford under the supervision of Prof. Christina Goldschmidt, where I was also a Stipendiary Lecturer at St. Hugh's College. 

My research is in discrete probability. The common denominator of my projects is that they involve creative sampling procedures that, combined with tools from (stochastic) analysis, allow me to study the large-scale structure of the random tree or graph. Whether I am obtaining a large deviations principle, solving a counting problem with the probabilistic method or proving a metric space scaling limit, I always devote most attention to finding a smart way of sampling that unlocks the result that I am after. This approach has allowed my coauthors and I to answer questions in both discrete probability and probabilistic combinatorics, asked by for example Svante Janson, Alex Scott, Colin McDiarmid, Gordon Royle and Paul Erdős. 


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You can find me in office 446 in the Bernoulliborg

PhD position

I will be recruiting a PhD student to start in 2024 or early 2025. Do you want to work on discrete probability and do you want to live in one of the best small cities in the world? Or do you know someone suitable? Don't hesitate to get in touch! More info on the job posting can be found here

You can also contact me if you would like to do a bachelor or master project on a topic related to discrete probability.


In term 2b I will be teaching the new graduate course Combinatorial Mathematics B. I will cover various models for random trees and graphs and I will discuss the probabilistic tools needed to study them. 


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