Post-doc Positions (Finnish Center for Artificial Intelligence)

As part of Finnish Center for Artificial Intelligence FCAI (fcai.fi), we are looking for people with a strong background in machine learning, in particular reinforcement learning, to work on two topics:

  1. Closing Sim-to-Real Gap

To study future sustainable mobility, FCAI is building Sustainable Mobility and Autonomous Systems Virtual Laboratory. The virtual laboratory will allow studying effects of autonomous traffic starting from control of individual vehicles, to their environmental effects such as pollution and noise, as well as their socio-economic effects. The virtual laboratory will integrate several simulators including an autonomous vehicle simulator, as well as other simulators modeling relevant phenomena.

When relying on simulation models for data-driven analytics, a central issue is the reality gap, the difference between a simulation model and the real world. In practice, simulation parameters need to be inferred often from scarce real-world data. However, in addition to this calibration problem, the simulation model is unlikely to capture all real-world phenomena. Thus, addressing the sim-to-real problem requires also determining this residual gap in order to compensate for it. This problem requires data-efficient probabilistic methods that are simultaneously expressive.

2. Design of Maximally Autonomous Collaborative AI Systems

Designing AI-agents that perform sequential tasks for users is challenging, especially in cases where the underlying goal is difficult to specify. The more automatically the AI system can operate, the more it can help us – but if it has not understood what we want, we would not want the help. The problem is compounded when the user is unable to provide ideal demonstrations to the agent due to some constraints. Such scenarios arise in many robotic applications, where providing optimal demonstrations is not straightforward.

We develop methods that can infer the underlying goal of a task through minimal user interaction and feedback. This requires the use of Bayesian experimental design techniques in combination with inference methods and interactive learning.

Prior experience on robotics applications is a plus though not necessary – the principles are broadly applicable beyond robotics.

Research environment

FCAI’s internationally acclaimed research community provides you with a broad range of possibilities and Finland is a great place for living – it has been listed as the happiest country in the world for the fourth year running.

To apply

The deadline for the applications is January 30. Read more and apply here: https://fcai.fi/we-are-hiring
There are also other interesting topics open at FCAI as part of the same call.