PhD Candidate on Reinforcement Learning for Controlling Critical Infrastructure

How can AI contribute to safe and efficient operation of critical infrastructure? Infrastructure such as railways, the electric grid, and air traffic control faces increasing usage, making the networks harder to operate. In this project, you will investigate how machine learning methods can be used in such situations, possibly together with a human operator.

Recent success in applying deep reinforcement learning methods to e.g. Atari games or the boardgames of Go suggest that this technology is able to find complex strategy by learning from data obtained through trial and error. When applying such methods to critical infrastructure, new questions arise. Can machine learning tools be combined with conventional optimisers to improve safety and data efficiency? Can complex, structured decisions be made jointly by a human operator and an artificial agent? Can such algorithms deal with hierarchies in decision making, and how can decisions or models be explained and verified?

Within the AMLab research group at the university of Amsterdam, we are looking for a PhD candidate interested in addressing (some of) these challenges within a European project, “AI for real networks”, that includes knowledge institutes and industrial partners with expertise ranging from core machine learning research to the three application domains of electric grid operation, railway operation, and air traffic control, across 8 EU countries.

What are you going to do?

You will perform research in the area of reinforcement learning and its application to the control of critical infrastructure.

Tasks and responsibilities

You are expected:

• to invent, evaluate and describe novel algorithms for improving operation of critical infrastructure using machine learning;
• to integrate such algorithms into experimental and application scenarios, and evaluate them according to indicators including effectiveness, efficiency, and useability;  
• to present research results at international conferences, workshops, and journals;
• to become an active member of the research community and to collaborate with other researchers, both within and outside the AI4RealNet project and the Informatics Institute;
• to pursue and complete a PhD thesis within the appointed duration of four years;
• to assist in teaching activities, such as teaching labs and tutorials or supervising bachelor and master students.

What do you have to offer?

Your experience and profile:

• You have the research skills to address scientific and technical problems in the field of artificial intelligence;
• You are eager to tackle complex scientific problems, and you are able to implement and evaluate machine learning algorithms, e.g. using Python deep learning toolkits;
• You are able to work well in teams;
• You possess a master’s degree in computer science, Artificial Intelligence, Machine Learning, Operations Research, or a closely related field;
• You are able to communicate fluently in written and spoken English.

Familiarity and interests with reinforcement learning is preferable.

Our offer

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 as soon as possible. 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, 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 PhD Candidate 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.

About us

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 candidate will be employed full time at UvA, within the Amsterdam Machine Learning Lab (AMLab) research group that is headed by Dr. Jan-Willem van de Meent and Prof. Max Welling. Daily supervision will be provided by 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 setting.

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

Any questions?

Do you have any questions, or do you require additional information? Please contact:

• E: Herke van Hoof, assistant professor