Assistant/Associate Professor Causal Reinforcement Learning

Artificial Intelligence (AI) and machine learning (ML) are literally changing the world. However, many AI and ML techniques employ statistical models that do not take this into account. This can lead to a plethora of problems, of which performance lower than expected is perhaps the most benign. In contrast, causal models try and capture the true effect of interventions or ‘actions’, while reinforcement learning deals with understanding the long-term outcomes of such actions over time. Will you build on these techniques to set up a research program on how intelligent systems can better understand the true outcome of their actions and predictions? 

For the Assistant/Associate Professor position, TU Delft welcomes candidates with interest in exploring the intersection between causal inference and reinforcement learning or other forms of sequential decision making, with a particular preference for applications in any of the fields of health, safety/security, energy transition and sustainability.

The successful candidate will be embedded in TU Delft’s vibrant AI community (http://ai.tudelft.nl), and have the opportunity to collaborate in the context of local networks, such as the “Convergence initiative” (https://convergence.nl) or the ELLIS Unit Delft (http://ellis.tudelft.nl), as well as extending their own international network.  

Interested candidates should apply before March 31, 2023. 

Find the full job description and all details about the application process here.