Do you enjoy solving challenging machine learning problems on complex real-world data, and are you interested in the fintech (financial technology) domain? The AMLab group at the university of Amsterdam is looking for two PhD candidates on topics in this field. Each candidate will work on one of two subprojects, that have a main focus on causal machine learning and reinforcement learning, respectively. The goal is to advance research in both fields while also evaluating and balancing its practical feasibility. The research falls within a collaboration between the University of Amsterdam and Adyen.

In project 1 we will focus on learning causal drivers of user behaviour in transaction approval pipelines through reusing existing data or by designing new A/B tests. For example, when deciding which options to use to authorize a transaction, we might want to optimize the trade-off between ensuring that the transaction is legitimate and creating unnecessary friction for the users. Estimating the causal effect of each choice on different sets of users allows us to optimize this decision, but designing and implementing A/B tests can be expensive and prone to selection bias. In this project, we will explore how to accurately and sample-efficiently learn causal relations by reusing data from previously run A/B tests and observational data, as well as design cheaper and more accurate A/B tests that can help us estimate the intended causal effects.

Project 2 aims to use and develop novel reinforcement learning (RL) techniques to improve the decision making about transactions. For example, should a transaction be marked as fraudulent, and how should the transaction best be presented to a payment card issuer? While these are practical problems, they pose fundamental challenges to learning algorithms. For example, how can we handle a complex, combinatorial, and constraint action space? How can we learn and evaluate policies on off-line data only? And how can we learn a solution that allows for a flexible trade-off between different metrics?

What are you going to do?
You will perform machine learning research with complex real-world data (and possibly synthetic proxies). You are able to work within a team, while also pro-actively tackling research challenges with input and guidance from your advisors. You will be working closely with faculty members from UvA’s AMLab as well as engineers from Adyen.

Tasks and responsibilities:

• invent, evaluate and describe novel algorithms for improving causal effect estimation, prediction and decision-making in the fintech domain using machine learning;
• integrate such algorithms into experimental and application scenarios, and evaluate them;
• present research results at international conferences, workshops, and journals;
• become an active member of the research community and to collaborate with other researchers, both at the Informatics institute and at Adyen, as well as externally;
• pursue and complete a PhD thesis within the appointed duration of four years;
• assist in teaching activities, such as teaching labs and tutorials or supervising bachelor and master students;

Your experience and profile (below are examples you don’t need to use them):

• MSc in computer science, artificial intelligence, statistics, econometrics, or a related field;
• You have experience with artificial intelligence, statistics or data science, and you are not afraid of mathematics.
• You have a good academic record and you enjoy tackling complex scientific problems;
• You are able to implement and evaluate algorithms, e.g. using Python or R;
• You are able to work well in teams and communicate fluently in written and spoken English.

Familiarity with either causal methods or reinforcement learning is preferred but not a requirement. Likewise, interest in the FinTech domain is preferred but not a requirement.

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 to be discussed, but preferably between May and September 2024. 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's students.

The gross monthly salary, based on 38 hours per week and dependent on relevant experience, ranges between € 2,770 in the first year to € 3,539 in the last year (scale P). UvA additionally offers an extensive package of secondary benefits, including 8% holiday allowance and a year-end bonus of 8.3%. The UFO profile Promovendus is applicable. A favourable tax agreement, the ‘30% ruling’, may apply to non-Dutch applicants. The Collective Labour Agreement of Universities of the Netherlands is applicable.

Besides the salary and a vibrant and challenging environment at Science Park, we offer you multiple fringe benefits:

• 232 holiday hours per year (based on fulltime) and extra holidays between Christmas and 1 January;
• Multiple courses to follow from our Teaching and Learning Centre;
• A complete educational program for PhD students
• Multiple courses on topics such as leadership for academic staff;
• Multiple courses on topics such as time management, handling stress and an online learning platform with 100+ different courses;
• 7 weeks birth leave (partner leave) with 100% salary;
• Partly paid parental leave;
• The possibility to set up a workplace at home;
• A pension at ABP for which UvA pays two third part of the contribution;
• The possibility to follow courses to learn Dutch;
• Help with housing for a studio or small apartment when you’re moving from abroad.

Are you curious to read more about our extensive package of secondary employment benefits, take a look here.

Faculty of Science

The University of Amsterdam (UvA) is the Netherlands' largest university, offering the widest range of academic programmes. At the UvA, 42,000 students, 6,000 staff members and 3,000 PhD candidates study and work in a diverse range of fields, connected by a culture of curiosity.

The Faculty of Science (FNWI) has a student body of around 8,000, as well as 1,800 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 mission of the Informatics Institute (IvI) is to perform curiosity-driven and use-inspired fundamental research in Computer Science. The main research themes are Artificial Intelligence, Computational Science and Systems and Network Engineering. Our research involves complex information systems at large, with a focus on collaborative, data driven, computational and intelligent systems, all with a strong interactive component.

The PhD candidates will be employed full time at UvA, within the AMLAB (Amsterdam Machine Learning Lab) research group that is headed by Dr. Jan-Willem van de Meent and Prof. Max Welling. Daily supervision will be provided by Sara Magliacane and Herke van Hoof. The AMLAB consists of about 30 people working on various topics within machine learning, including deep learning, reinforcement learning, causality, geometric learning, Bayesian methods, etcetera. Within the lab, collaboration is stimulated, as is interaction between group members in formal settings (e.g. seminars) as well as informal settings.

Adyen is the payments platform of choice for the world’s leading companies, delivering frictionless payments across online, mobile and in-store channels. It is the only provider of a modern end-to-end infrastructure, connecting directly to Visa, Mastercard, and consumers’ globally preferred payment methods. With offices around the world, Adyen serves nine of the 10 largest U.S. internet companies and many worldwide retailers. Customers include Facebook, Uber, Dafiti, 99taxis, Rappi and Spotify.

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