Doctoral Researcher in Reinforcement Learning (2 positions)

About the role

Aalto University's Cyber-physical Systems Group in the School of Electrical Engineering is seeking two doctoral researchers for an ERC Starting Grant-funded project on continual reinforcement learning for real-world systems. The project combines trajectory-centric objectives with adaptive, context-dependent policies, and the two researchers will work together to integrate both approaches into a single algorithm. The work is mainly theoretical, though the university's robot lab allows practical evaluation on robot arms or quadruped robots.

Key responsibilities

• Develop theory for trajectory-centric stochastic optimization under non-ergodic dynamics
• Implement practical RL algorithms that optimize the long-term performance of individual agents
• Develop change-detection algorithms that infer when a policy is no longer valid
• Implement efficient policy-adaptation algorithms with safety guarantees
• Integrate these advances into state-of-the-art RL algorithms
• Validate the algorithms in simulations and hardware experiments

Required profile

• Master's degree in computer science, mathematics, electrical engineering or a related field
• Fluent written and spoken English
• Ability to work independently and collaboratively in a research team
• Strong background in one or more of: stochastic processes (ideally with ergodicity theory), reinforcement learning, dynamic programming or Markov decision processes

Required skills

• Python programming
• Reinforcement learning and dynamic programming

What we offer

• Fully funded doctoral position, fixed term on the school's 2+2 model (two years initially, then two more after a mid-term review)
• Starting salary of 3,143 EUR per month
• Start in January 2027 or as mutually agreed
• Collaboration within a young, internationally connected research group, with possible research visits to partner institutions

Applications close on 23 October 2026 and must include a motivation letter stating which position is applied for, a CV with two referees, and copies of academic transcripts and diplomas. Aalto employees apply through the internal HR system; students and visitors apply through the university's open positions page.