Doctoral Researchers in Reinforcement Learning
Join a cutting-edge project on continual reinforcement learning at Aalto University.
Best for:Best for candidates with a strong background in reinforcement learning and programming skills.
Overview
Aalto University is seeking two motivated doctoral researchers to join the Cyber-physical Systems Group within the School of Electrical Engineering. This ERC Starting Grant-funded project focuses on developing reinforcement learning algorithms that adapt to real-world systems, addressing challenges such as non-ergodic dynamics and policy adaptation. Candidates will engage in both theoretical and practical aspects of reinforcement learning, with opportunities for experimental validation in the Aalto robot lab. Successful applicants will contribute to advancing the field through innovative research and collaboration.
What you'll do
- Develop theoretical frameworks for trajectory-centric stochastic optimization under non-ergodic dynamics.
- Implement practical reinforcement learning algorithms to enhance long-term performance of agents.
- Create change detection algorithms to identify when policies require adaptation.
- Design efficient policy-adaptation algorithms with safety guarantees.
- Integrate theoretical advancements into state-of-the-art reinforcement learning algorithms.
- Validate algorithms through simulations and practical experiments in the Aalto robot lab.
Requirements
Degree required: Master’s degree in computer science, mathematics, electrical engineering, or related fields
Degree offered: PhD
Language: English; fluent proficiency required
Instruction: English
- Strong background in stochastic processes and reinforcement learning
- Proficiency in programming, particularly in Python
- Ability to work independently and collaboratively in a research team
- Fluent written and verbal communication skills in English
- Open to all qualified candidates regardless of background
- Candidates must meet the admission criteria for doctoral studies at Aalto University
Funding & terms
How to apply
Deadline: 2026-10-23T23:59:59 (Europe/Helsinki)
To apply, submit your application through the recruitment site by the deadline. Include a motivation letter, CV with at least two referees, and copies of your academic transcripts and diplomas.
- Motivation letter
- CV
- Bachelor’s and Master’s degree transcripts and diplomas
Contact
Dominik Baumann· Supervisor
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