PostDoc on Reinforcement Learning in the Real World

PostDoc on Reinforcement Learning in the Real World

Published Deadline Location
14 Dec 17 Jan Delft

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Do you have what it takes to push reinforcement learning beyond the realm of games? Reinforcement learning (RL) is a promising approach to learn to control decision making problems that extend over time, but so far applications have been largely limited to synthetic settings such as games. In an attempt to overcome this, in a collaboration with and the University of Amsterdam, the Mercury Machine Learning Lab was founded to develop more usable RL and other machine learning techniques. Motivated by real-world problems faced in industry, we will investigate fundamental problems in reinforcement learning.

Job description

In the Mercury Machine Learning Lab, researchers from the University of Amsterdam (UvA) and Delft University of Technology (TU Delft) will be working together with 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. 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.

This PostDoc position will focus on reinforcement learning. Possible directions of interest are:

  • Bayesian reinforcement learning
  • Multiagent / concurrent reinforcement learning
  • Causal reinforcement learning

The approach could be more empirical (e.g., using deep reinforcement learning), or more theoretical. Interested candidates are encouraged to contact Matthijs Spaan and Frans Oliehoek to discuss potential directions.

The candidate is expected to play a leading role in the lab, working together with the 2 PhD students employed at TU Delft that focus on reinforcement learning, as well as collaborating with colleagues in the larger lab.


Delft University of Technology (TU Delft)


The candidate should have:

  • a PhD degree in Artificial Intelligence (AI) or closely related topics in computer science, mathematics, or physics.
  • an excellent track record in the general area of machine learning,
  • excellent math skills.
  • a thorough understanding of reinforcement learning.
  • fluency in English

The ideal candidate:

  • is interested in working in a multi-disciplinary project also involving causal inference, recommender systems and natural language processing
  • has strong coding skills and experience with deep learning frameworks
  • is a strong communicator, and can work well in a team, and willing to interact with both business and academic advisors
  • is self-motivated to do cutting-edge research


Conditions of employment

Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities. The TU Delft offers a customisable compensation package, a discount on health insurance and sport memberships, and a monthly work costs contribution. Flexible work schedules can be arranged.

For international applicants we offer the Coming to Delft Service and Partner Career Advice to assist you with your relocation. An International Children's Centre offers childcare and there is an international primary school.


Delft University of Technology

Delft University of Technology is built on strong foundations. As creators of the world-famous Dutch waterworks and pioneers in biotech, TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society. For generations, our engineers have proven to be entrepreneurial problem-solvers, both in business and in a social context. At TU Delft we embrace diversity and aim to be as inclusive as possible (see our Code of Conduct). Together, we imagine, invent and create solutions using technology to have a positive impact on a global scale.

Challenge. Change. Impact! 


Faculty Electrical Engineering, Mathematics and Computer Science

The Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) brings together three disciplines - electrical engineering, mathematics and computer science. Combined, they reinforce each other and are the driving force behind the technology we use in our daily lives. Technology such as the electricity grid, which our faculty is helping to make future-proof. We are also working on a world in which humans and computers reinforce each other. We are mapping out disease processes using single cell data, and using mathematics to simulate gigantic ash plumes after a volcanic eruption. There is plenty of room here for ground-breaking research. We educate innovative engineers and have excellent labs and facilities that underline our strong international position. In total, more than 1,100 employees and 4,000 students work and study in this innovative environment.

Click here to go to the website of the Faculty of Electrical Engineering, Mathematics and Computer Science.


  • Postdoc
  • Engineering
  • €2836—€4474 per month
  • Doctorate
  • TUD01798


Delft University of Technology (TU Delft)

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Mekelweg 2, 2628 CD, Delft

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