Job Overview

PhD Position in Causality for Domain Adaptation and Optimization

Are you passionate about causality and its applications for domain adaptation and optimization? We have a vacancy for a PhD candidate 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) will be working together with data scientists from Booking.com to develop the statistical and machine learning foundations for a new generation of recommendation systems.

Motivated by real-world problems faced in industry that involve domain adaptation and optimization, we will investigate fundamental problems regarding generalization and bias removal in data analysis from a causal perspective.

As part of the MMLL initiative, the University of Amsterdam is inviting applications for a fully funded PhD position in causality for domain adaptation and optimization supervised by prof.dr. Joris Mooij.

Wat are you going to do?

As a PhD student, you will be expected to:

• develop, study and apply machine learning techniques within the context of the research project, under supervision of the promotor and a data scientist from Booking.com;
• complete and defend a PhD thesis within the official appointment duration of four years;
• publish research results in top-tier international journals and present at leading conferences;
• collaborate with other MMLL and causality researchers;
• assist in relevant teaching and knowledge dissemination activities.

What do you have to offer?

• A Master’s degree in mathematics, statistics, computer science, artificial intelligence, computer science, or closely related area;
• a strong background in artificial intelligence / machine learning / modern statistics;
• excellent mathematical skills (in particular in probability theory, statistics, calculus, and linear algebra);
• excellent programming skills;
• excellent communication, presentation and writing skills;
• an excellent command of English;
• commitment, perseverance and a cooperative attitude.

In addition, you:

• have an interest in causality and its applications for domain adaptation and optimization;
• have an appetite for understanding the machine learning problems relevant to Booking.com, and the desire to perform in-depth analyses of rich datasets;
• enjoy working in a multidisciplinary research environment;
• are highly motivated and creative.

Our offer

We offer an employment contract for 38 hours per week for the duration of four 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 four years). Your salary, depending on your relevant experience on commencement of the employment contract, ranges between €2,443 to €3,122 (scale P) 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.

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 newly established Mercury Machine Learning Lab. In this lab, researchers from the University of Amsterdam (UvA) and Delft University of Technology (TU Delft) will be working together with Booking.com on various improved recommendation systems. The collaboration provides the unique 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 will comprise six PhD candidates and two postdocs who will work on six different projects related to bias and generalisation problems over the course of the next five years. They will spend two days a week in the office of Booking.com 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.

Questions?

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

• Juliane Steinhardt
• T. +31 (0)20 525 7571

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). We will accept applications until 31 January 2022.

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

• a curriculum vitae;
• a motivation letter that motivates your choice for this specific position;
• an electronic copy of your Master’s thesis (or, if this is not yet finished, your Bachelor’s thesis);
• a complete record of Bachelor and Master courses (including grade transcripts and the explanation of the grading system used by your university);
• a list of publications, if applicable;
• the names and contact information of two academic references (please do not include any recommendation letters).

The first round of application interviews will take place early February 2022.

How to Apply