Postdoctoral position in machine learning with a focus on reinforcement learning and model predictive control Full-time

Postdoctoral Position In Machine Learning With A Focus On Reinforcement Learning And Model Predictive Control

Are you interested in working with state-of-the-art machine learning methods with the support of competent and friendly colleagues in an international environment? Are you looking for an employer that invests in sustainable employeeship and offers safe, favorable working conditions? We welcome you to apply for a postdoctoral position at Uppsala University.

Uppsala University has a long tradition of successful research – among its alumni are 16 Nobel Prize laureates, including, most recently, Svante Pääbo. The University is unique when it comes to combining IT with wider research, from life sciences to the humanities.

The Department of Information Technology holds a leading position in both research and education at all levels. We are currently Uppsala University's third largest department, have around 350 employees, including 120 teachers and 120 PhD students. Approximately 5,000 undergraduate students take one or more courses at the department each year. You can find more information about us on the Department of Information Technology website.

At the Division of Systems and Control, we develop both theory and concrete tools to design systems that learn, reason, and act in the real world based on a seamless combination of data, mathematical models, and algorithms. Our research integrates expertise from machine learning, optimization, control theory, and applied mathematics, spanning diverse application domains such as medicine, energy systems, biomedical systems, neuroscience, and safety and security.

We have a wide network of long-standing international collaborators all around the world, for example at the University of Cambridge, University of Oxford, Imperial College London, University of Sydney, University of Newcastle and Aalto University.

Duties: This project focuses on developing, analyzing, and applying new methods in reinforcement learning and model predictive control (MPC), both stochastic and deterministic formulations. The focus will be on developing methods for robust reinforcement learning and/or MPC formulations. We are particularly interested in settings where the cost or reward function is non-ergodic. In these situations, the expected costs/rewards do not capture the behavior of individual rollouts, which calls for new constructions. We will develop and analyze generally applicable algorithms and models together with our collaborators. The postdoctoral researcher will be jointly supervised by Assistant Professor Dominik Baumann (Aalto University) and when it comes to the MPC aspects, we will collaborate with Assistant Professor Johannes Köhler at Imperial College London.

Technical building blocks may include reinforcement learning, state-space models, MPC, deep learning, and probabilistic modeling in general.

The position may include teaching up to 20% depending on availability and interest. You are expected to be able to teach in Swedish or English.

Requirements: PhD degree in machine learning, control, signal processing, or another nearby relevant area or a foreign degree equivalent to a PhD degree in machine learning, control, signal processing. The degree needs to be obtained by the time of the decision of employment. Priority will be given to applicants who have completed their degree no more than three years before the deadline for applications. Due to special circumstances, the degree may have been obtained earlier. The three-year period can be extended due to circumstances such as sick leave, parental leave, duties in labor unions, etc.

We are looking for candidates with:

• a strong interest in and experience in developing new methods in reinforcement learning and/or model predictive control,
• ability to communicate technical material effectively in oral and written form (English),
• good working knowledge of programming (preferably in Python).
• personal qualities, such as a high level of creativity, accuracy and/or a structured approach to problem solving are essential.

Publications at leading conferences in machine learning and/or leading journals in control engineering are a big plus.

Additional qualifications: Experience of working with companies is good. As a person, you are creative, meticulous and have a structured approach. When selecting applicants, we will assess their ability to independently drive their work forward, to collaborate with others, to have a professional approach and to analyze and work with complex problems. Great importance will be placed on personal qualities and personal suitability.

The application must contain:

1. A curriculum vitae (CV),
2. List of publications,
3. Description of your current and previous research (max. 1 page) and proposals for future research (max. 1 page),
4. Contact information for two references.

About the employment: The employment is a temporary position of 2 years according to central collective agreement. Full time position. Starting date October 1, 2026 or as agreed. Placement: Uppsala.

For further information about the position, please contact: Professor Thomas Schön, 018 – 471 25 94, thomas.schon@uu.se

Please submit your application by August 21, 2026, UFV-PA 2026/1965.

Uppsala University is a broad research university with a strong international position. The ultimate goal is to conduct education and research of the highest quality and relevance to make a difference in society. Our most important asset is all of our 7,600 employees and 53,000 students who, with curiosity and commitment, make Uppsala University one of Sweden's most exciting workplaces.

Read more about our benefits and what it is like to work at Uppsala University https://uu.se/om-uu/jobba-hos-oss/

The position may be subject to security vetting. If security vetting is conducted, the applicant must pass the vetting process to be eligible for employment.