Postdoc Position in Causal Inference and Machine Learning

Faculty/Services:  Faculty of Science
Educational level:  PhD
Function type:  Academic Staff
Closing date:  12.02.2023
Vacancy number:  9461

Do you enjoy: Are you a machine learning researcher or statistician who is passionate about causality and its applications?

We have a vacancy for a postdoctoral researcher in the recently established Mercury Machine Learning Lab (MMLL).

In this lab, researchers from the University of Amsterdam (UvA) and Delft University of Technology (TU Delft) are working together with data scientists from to work on problems dealing with missing data, causality, distribution shifts, contextual bandits, and reinforcement learning. Inspired by real-world problems faced in industry that involve domain adaptation, estimation and optimization, we will investigate fundamental scientific problems regarding generalization and bias removal from a causal perspective.

As part of the MMLL initiative, the University of Amsterdam is inviting applications for a postdoctoral researcher in causality under supervision of prof.dr. Joris Mooij.

What does this job entail?

You will be expected to:

 develop, study and apply machine learning techniques within the context of the research project, in collaboration with data scientists from and under supervision of prof. dr. Mooij;

– publish research results in top-tier international journals and present at leading conferences;

– assist with the research and the supervision of PhD students involved in the MMLL initiative;

– collaborate with other MMLL and causality researchers;

– assist in relevant teaching and knowledge dissemination activities.

What do you have to offer?

– A PhD degree (or equivalent qualification) on a topic in machine learning / statistics;

– an exceptional scientific track record, documented by publications at first-tier journals and conferences;

– a strong research background in (topics related to) causality, domain adaptation and stochastic optimization;

– excellent mathematical and programming skills;

– excellent communication, presentation and writing skills;

– an excellent command of English;

– commitment, perseverance and a cooperative attitude.

In addition, you:

– have a keen interest in causality and its applications;

– get inspiration from working on mathematical formalizations of real-world problems;

– enjoy working in a multidisciplinary research environment;

– are highly motivated and creative.

What can we offer you?

We offer a temporary employment contract for 38 hours per week for the duration of 4 years (the initial contract will be for a period of 12 months and after satisfactory evaluation it will be extended for a total duration of 4 years).

Your salary, depending on your relevant experience on commencement of the employment contract, ranges between € 2,790 to € 4,402 (scale 10) gross per month on the basis of a full working week of 38 hours. This sum does not include the 8% holiday allowance and the 8.3% year-end allowance. The Collective Labour Agreement for Dutch Universities (CAO NU) is applicable. A favourable tax agreement, the ‘30% ruling’, may apply to non-Dutch applicants.

About us

The University of Amsterdam is the largest university in the Netherlands, with the broadest spectrum of degree programmes. It is an intellectual hub with 39,000 students, 6,000 employees and 3,000 doctoral students who are all committed to a culture of inquiring minds.

A prominent research topic at the UvA is Artificial Intelligence. The UvA is part of the AI Technology for People initiative, where it teams up with several other key players within the Amsterdam region. Together they will invest 1 billion euros in the development of responsible AI technologies over the next ten years by setting up research programmes, attracting top scientists and educating students with state-of-the-art knowledge of AI. The UvA was selected by the European Laboratory for Learning and Intelligent Systems (ELLIS) as an Excellence Centre for AI to help keep in Europe talent in machine learning and related AI research fields. The UvA is also involved in various labs of the Innovation Centre for AI (ICAI), which promotes public-private partnerships in the general area of AI.

One of these ICAI labs is the Mercury Machine Learning Lab. In this lab, researchers from the University of Amsterdam (UvA) and Delft University of Technology (TU Delft) are working together with on various improved recommendation systems. The collaboration provides the opportunity to test AI techniques in the real world, allowing new machine learning methods to be safely developed for wide application, for example in mobility, energy or healthcare. The UvA researchers participating in the MMLL have different areas of expertise and are affiliated with various research institutes of the Faculty of Science. Prof. dr. De Rijke specializes in information retrieval and is affiliated with the Informatics Institute. Prof dr. Mooij specializes in causality and is affiliated with the Korteweg-De Vries Institute for Mathematics. Dr. Titov and dr. Aziz both specialize in NLP and are affiliated with the Institute for Logic, Language and Computation. The researchers affiliated with the TU Delft that are involved in the MMLL are dr. Spaan and dr. Oliehoek, who both specialize  in reinforcement learning.

In addition to the existing researchers, the Mercury Machine Learning Lab comprises six PhD candidates and two postdocs who work on six different projects related to bias and generalisation problems over the course of five years. They spend two days a week in the office of in Amsterdam to do research and actively participate in related streams of experimentation to test their hypotheses. More information about the Mercury Machine Learning Lab and the related projects can be found on the MMLL website.

Want to know more about our organisation? Read more about working at the University of Amsterdam.

Any questions?

If you have any questions about the position, please contact (during office hours):

Joris Mooij, tel. +31 (0)20 525 8426 and email

Job application

If you feel the profile fits you, and you are interested in the job, we look forward to receiving your application. You can apply online via the link below (and please do not apply via email).

Applications (CONSISTING OF A SINGLE .pdf FILE) should include:

  • a curriculum vitae;
  • a motivation letter;
  • a list of publications;
  • a statement of your research experience and interests;
  • an electronic copy of (or link to) your PhD thesis;
  • a complete record of Bachelor and Master courses (including grade transcripts and the explanation of the grading system used by your university);
  • (URL pointing to) your most original publication;

the names and contact information of two academic references (please do not include any recommendation letters).