A fully funded PhD opportunity at Linköping University focusing on reinforcement learning, control theory, and world modeling for partially observable dynamical systems. The position is part of the Zenith research project.

Important Information

Linköping University invites applications for a fully funded PhD position in Reinforcement Learning for Control of Partially Observable Dynamical Systems. With over 40,000 students and staff, LiU is recognized for innovative, impact-driven research.

This PhD position is connected to the Zenith project, focusing on advancing reinforcement learning algorithms capable of controlling systems where the agent does not have full visibility of the environment. The position is rooted in the Division of Automatic Control, a globally recognized center for research in autonomous systems, modeling, optimization, and sensor fusion.

Project Focus

The research addresses one of the most challenging areas in RL—control under partial observability. The project will explore several key research directions:

• Efficient World Modeling:
  Developing predictive and compact representations of the environment using both model-free and model-based RL methods. Special attention will be given to learning effective models from limited observed data.

• Algorithm Development:
  Designing RL algorithms that integrate world models for planning, prediction, and control. The goal is to improve robustness, generalization, and sample efficiency in continuous state and action spaces.

You may read more about the project here:
https://liu.se/en/research/reinforcement-learning-for-partially-observable-dynamical-systems

The candidate will devote most of their time to research and doctoral studies, with the possibility of teaching duties for up to 20% of working hours.

Required Qualifications

Candidates must hold (or be completing soon) a Master’s degree in:

• Electrical Engineering

• Computer Science

• Engineering Physics

• Applied Mathematics
  —or closely related fields

Additional required competencies:

• Strong background in control theory

• Familiarity with reinforcement learning

• Proficient programming skills

• Excellent English (spoken and written)

Meritorious skills:

• Knowledge of ML, optimization, statistics

• Experience in Python

Work Environment

You will join the Division of Automatic Control, known for research excellence and international collaborations. More information is available at:

• Division Page: https://liu.se/en/organisation/liu/isy/rt

• ISY Jobs: https://liu.se/en/article/open-positions-at-isy

Employment Terms

• Duration: 4 years full-time (may extend to 5 years with teaching duties)

• Initial contract: 1 year, renewable based on progress

• Benefits: Swedish social security, healthcare allowance (SEK 2,500/year), parental leave, pension contributions

Background screening may be conducted before employment.

How to Apply

Applications must be submitted via the official portal before December 5, 2025. Late submissions will not be considered.

The application must include:

• CV

• Relevant certificates and transcripts

• Any additional required documents per portal instructions

Linköping University values diversity and welcomes applicants from all backgrounds.

Contact Persons

• Farnaz Adib Yaghmaie (Assistant Professor) – farnaz.adib.yaghmaie@liu.se

• Martin Enqvist (Associate Professor) – +46 (0)13 281393

• Karin Blomdahl (HR Coordinator) – karin.blomdahl@liu.se

Disclaimer 

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