2 Doctoral Researchers in Reinforcement Learning

Aalto University is where science and art meet technology and business. We shape a sustainable future by making research breakthroughs in and across our disciplines, sparking the game changers of tomorrow and creating novel solutions to major global challenges. Our community is made up of 16 000 students and 5 200 employees, including 446 professors. Our campus is in Espoo, Greater Helsinki, Finland. Diversity is part of who we are, and we actively work to ensure our community's diversity and inclusiveness. This is why we warmly encourage qualified candidates from all backgrounds to join our community.

We are currently seeking two highly motivated doctoral researchers to join the Cyber-physical Systems Group at Aalto University's School of Electrical Engineering for an ERC Starting Grant-funded project focused on continual reinforcement learning for real-world systems. The grant provides a stable, well-resourced four-year research environment to tackle a problem that classical RL theory is not built for: real systems don't reset, failures can be irreversible, and the real world keeps changing.

Standard RL finds policies by optimizing over many hypothetical futures. Under non-ergodic dynamics, such an average may differ arbitrarily from what the individual agent experiences as it lives out one trajectory over time. Furthermore, RL typically seeks a time-invariant policy that cannot adapt to a changing environment. This project addresses both challenges simultaneously, combining trajectory-centric objectives with adaptive, context-dependent policies. This enables autonomous vehicles to adapt to seasonal changes over years, manufacturing systems to evolve with production demands without downtime, and medical monitoring to personalize to patients over decades.

The successful candidates will develop fundamental theory and practical algorithms that move reinforcement learning closer to real-world systems. Position 1 will focus on trajectory-centric optimization,