2 Doctoral Researchers in Reinforcement Learning

Aalto; Espoo; On-site; EUR 32,000 - 38,000; Full time

Benefits offered by this job

Fully funded position

Fixed 4-year term

Competitive salary

International collaborations

Job summary

Aalto University invites applications for two Doctoral Researchers in Reinforcement Learning within the Cyber-physical Systems Group of the School of Electrical Engineering. The ERC Starting Grant project aims to address continual RL for real-world systems that do not reset and keep changing, offering a four-year, fully funded research environment.

Position 1 emphasizes trajectory-centric optimization, Position 2 focuses on adaptive policies, with joint integration into a single RL algorithm.

Qualifications

• Master’s degree in computer science, mathematics, electrical engineering, or related fields.
• Fluent written and verbal communication skills in English.
• Ability to work both independently and collaboratively as part of a research team.

Responsibilities

• Develop theory for trajectory-centric stochastic optimization under non-ergodic dynamics.
• Implement practical RL algorithms that optimize long-term performance of agents.
• Develop change-detection algorithms to infer when a policy must be adapted.
• Implement policy-adaptation algorithms with safety guarantees.
• Integrate advances into state-of-the-art RL algorithms.
• Validate algorithms in simulation and hardware environments.

Skills

Reinforcement learning

Trajectory-centric optimization

Adaptive policies

Non-ergodic dynamics

Education

Master’s degree in CS/Math/EE

Job description

2 Doctoral Researchers in Reinforcement Learning

29.9.2026

Application closes on

23.10.2026

Unit

School of Electrical Engineering

Job category

Doctoral Researchers

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, Position 2 on adaptive policies, and both will work jointly to integrate the two approaches into a single RL algorithm. While the work is mainly methodological and theoretically focused, our Aalto robot lab offers the possibility to evaluate the algorithms through practical experiments, e.g., on robot arms or quadruped robots.

Research focus

This project sits at the intersection of two problems: connecting ergodicity theory to reinforcement learning is a very recent development, and enabling RL agents to safely detect and adapt to a changing environment is a timely and active research area. Combining trajectory-centric objectives and adaptive, context-aware policies is new territory. The two doctoral researchers will drive this forward from these two complementary angles and will work closely together to integrate both into a single algorithm:

• Developing theory for trajectory-centric stochastic optimization under non-ergodic dynamics;
• Implementing practical RL algorithms that optimize long-term performance of individual agents;
• Developing change detection algorithms to infer when a policy is no longer valid and needs to be adapted;
• Implementing efficient policy-adaptation algorithms with safety guarantees;
• Integrating those advances into state-of-the-art RL algorithms;
• Validating the algorithms in relevant simulation environments and hardware experiments.

Requirements

Eligible candidates should have

• Master’s degree in computer science, mathematics, electrical engineering, or related fields;
• Fluent written and verbal communication skills in English;
• Ability to work both independently and collaboratively as part of a research team.

We are looking for candidates with a strong background in one or more of the following areas:

• Stochastic processes, ideally including a background in ergodicity theory;
• Reinforcement learning, dynamic programming, and Markov decision processes;

What we offer

• Fully funded doctoral researcher’s position at Aalto University, which is consistently ranked among the top universities in Europe;
• The position is fixed term and follows the school’s standard 2+2 model. It will be made initially for two years, with a six-month probationary period, and extended by two further years after a successful mid-term review, giving a total duration of four years;
• The position starts in January 2027 or as mutually agreed;
• The starting salary for a doctoral researcher is 3143 €/month;
• Opportunity to work on a high-impact research project;
• You will join a young and dynamic research group with ample opportunities for collaboration and exchange of ideas. The group is well connected internationally, with active research ties to institutions including RWTH Aachen University, KTH Stockholm, and the London Mathematical Laboratory, among others, and there is potential for research visits to these and other partners over the course of the PhD.

Want to know more about us and your future colleagues? You can watch these videos:

Finland is a great place for living with or without family – it is a safe, politically stable and well-organized Nordic society. Finland is consistently ranked high in quality of life and was listed again as the happiest country in the world: World Happiness Report