PhD Position on Mathematical Foundations for Explainable AI

Are you highly motivated to do PhD research in mathematical machine learning with special emphasis on mathematical foundations for explainable AI If yes the Korteweg-de Vries Institute for Mathematics at the University of Amsterdam is looking for you!

Join Us!

Are you interested in artificial intelligence and machine learning and do you want to develop new mathematics with a positive impact The stochastics group of the Korteweg-de Vries Institute for Mathematics at the University of Amsterdam is inviting applications for a PhD position in mathematical machine learning. The position is part of the research project Mathematical Foundations for Explainable AI funded by the Dutch research council (NWO). You will be part of a team with another PhD student and two consecutive postdoctoral researchers supervised by Dr. Tim van Erven.

This is what you will do

AI and machine learning models keep getting better but how they make their decisions often remains unclear because these depend on many incomprehensible model parameters that have been learned from data. For instance why does a machine learning model predict that it is unsafe to discharge a certain patient from the intensive care Or which characteristics make a machine learning model flag a certain bank transfer as potential money laundering The aim of this project is to develop new mathematical techniques that can explain AIs internal mechanisms by generating understandable explanations from machine learning models. We will achieve this together by creating the first mathematical framework for explainable AI and developing new explanation methods. This will involve using tools from mathematical machine learning theory to prove mathematical guarantees about the performance of such new explanation methods as well as programming to test out the methods and mathematical theory in experiments. (See example references 123 below for initial results.) During the PhD you will initially work on a pre-specified subproject of your choosing which allows you to develop your knowledge of the topic and research skills. As you gain experience you will increasingly shape your own research directions. You will collaborate closely with dr. Tim van Erven and other team members and connect with new (inter)national partners.

Tasks and responsibilities:

• Conduct research within the specified project as described above.

• Disseminate your research findings through publications in academic journals or peer-reviewed international conference proceedings and through presentations at international conferences.

• Participate in relevant seminars and engage in research collaborations locally and/or internationally.

• Participate in the Faculty of Science PhD training program.

• Participate in the departments educational programs assisting in teaching and supervision of undergraduate or Master students.

• Complete and defend a PhD thesis within the appointment duration of four years.

Example references:

For the application you are not expected to study the following references in depth but you may look into them for a high-level impression of the style of research.

1. H. Fokkema R. de Heide and T. van Erven. Attribution-based Explanations that Provide Recourse Cannot be Robust. Journal of Machine Learning Research vol. 24 no. 360 pp.1-37 2023.

2. H. Fokkema D. Garreau and T. van Erven.The Risks of Recourse in Binary Classification. Proceedings of the 27th International Conference on Artificial Intelligence and Statistics (AISTATS) vol. 238 pp..

3. H. Fokkema T. van Erven and S. Magliacane. Sample-efficient Learning of Concepts with Theoretical Guarantees: from Data to Concepts without Interventions. ArXiv: Preprint 2025.

What we ask of you

We are looking for an enthusiastic and driven candidate who meets the following requirements:

Your experience and profile:

• Educational background: You should have a Masters degree in mathematics or AI/computer science (with a strong mathematical component including writing formal mathematical proofs) to be completed before the start of the position. Other degrees with a strong mathematical component will also be considered.

• Interests: You should have a strong interest in mathematical machine learning theory and explainable AI. (This point is about your motivation not about the courses you have taken.)

• Programming skills: You should have very good programming skills in Python or similar which allow you to effectively test out new explanation methods in experiments.

• Communication skills: You should have excellent written and verbal communication skills in English.

• Teamwork and independence: You should be highly motivated and committed to your research. While you should be able to work independently you should also have a cooperative attitude and be willing to collaborate with the team members or other researchers.

Knowledge of mathematical machine learning theory or mathematical statistics is a plus as are extra-curricular activities in for instance student associations sports music etc. Prior knowledge of explainable AI is beneficial but not required.

This is what we offer you

A temporary contract for 38 hours per week for the duration of 4 years (the initial contract will be for a period of 18 months and after satisfactory evaluation it will be extended for a total duration of 4 years).The preferred starting date is between December 1 2025 and March 1 2026.This should lead to a dissertation (PhD thesis). We will draft an educational plan that includes attendance of courses and (international) meetings. We also expect you to assist in teaching undergraduates and master students.

The gross monthly salary based on 38 hours per week will range range from 2.901 in the first year to 3.707 (scale P) in the last addition you will receive an 8% holiday allowance and 83% end-of-year allowance. The Collective Labour Agreement of Universities of the Netherlands is applicable.

You will work in this team

TheFaculty of Science has a student body of around 8000 as well as 1800 members of staff working in education research or support services. Researchers and students at the Faculty of Science are fascinated by every aspect of how the world works be it elementary particles the birth of the universe or the functioning of the brain.

The Korteweg-de Vries Instituut voor Wiskunde (KdV Institute) is the mathematical research institute of the Faculty of Science of the Universiteit van Amsterdam. The KdV Institute offers a stimulating scientific environment in which research focuses mainly within the research programmes (1) Algebra Geometry and Mathematical Physics (2) Pure Applied and Numerical Analysis and (3) Stochastics and (4) Discrete Mathematics and Quantum Information. It also provides the lecturers and instructors for the mathematics teaching within the Science Faculty. The KdV Institute participates in the NWO research clusters GQT STAR NDNS and DIAMANT and in the Gravity programme NETWORKS. There is formal (and informal) cooperation with the Centrum Wiskunde & Informatica (CWI) the VU University and with Eurandom in Eindhoven. KdVI counts about 40 staff members and 50 postdocs and PhD students.

If you feel the profile fits you and you are interested in the position we look forward to receiving your application. You can apply online via the red button. We accept applications until and including October 13 2025.

For informal inquiries please contact:

• Tim van Erven via

Applications should include the following information (all files besides your CV should be submitted in one single pdf file):

• A detailed CV (resume);

• A letter of motivation (approximately 1 page) including an estimated starting date;

• A transcript of BSc and MSc grades;

• A sample of a mathematical proof you have written for example for a course or in a thesis;

• If available: a thesis or project report that demonstrates your academic writing skills;

• The name and email address of an academic reference who is willing to provide a reference letter upon request.

A knowledge security check can be part of the selection procedure.
(for details:national knowledge security guidelines)

Tentative application process:

• Application: we strive to provide initial notifications by October 17

• Round 1: online interview in the week of October 27

• Round 2: in-person interview in the week of November 10

Only complete applications received within the response period via the Apply button on this pagewill be considered.