项目介绍

2026年3月2日

We are looking for a postdoc to join our team at the Division of Systems and Control, Department of Electrical Engineering. Become part of our innovative group and contribute to exciting research in learning-based control within a collaborative and dynamic environment. 

About us 

At the department of Electrical Engineering research and education are performed in the areas of Communications, Antennas and Optical Networks, Systems and Control, Signal processing and Biomedical engineering, and Electric Power Engineering. We work with sustainable and smart solutions to societal challenges, such as energy efficiency and electrification in areas ranging from transport and production systems to communication solutions and biomedical engineering.

You will join a group within the Automatic Control unit of the Systems and Control division focusing on data-driven control methodologies.

About the research project  

Model-based control is arguably the prime framework to perform certifiably-safe regulation of dynamical systems. However, when dynamics are complex, nonlinear and partially unknown, such a model is typically obtained from observations by performing system identification — one notable example is given by Gaussian process regression to represent unknown dynamics for model predictive control. Despite the practical success, there are still many theoretical open questions regarding scalability, uncertainty bounds and deriving reliable safety guarantees. This project will aim at filling these gaps.

Who we are looking for 

The following requirements are mandatory: 

• A doctoral degree or an equivalent foreign degree in Engineering or Applied Mathematics. This eligibility requirement must be met no later than the time the employment decision is made  
• Strong written and verbal communication skills in English 
• Solid competence in control theory and system identification.  

You are expected to be somewhat accustomed to teaching, and to demonstrate good potential within research and education. 

The following experience will strengthen your application: 

• Knowledge in kernel-based learning and uncertainty quantification is a plus.

What you will do 

• Perform research
• Publish in peer-reviewed international journals and conferences
• Support Ph.D. candidates working in related problems. 

The position is meritorious for future roles in academia, industry, or the public sector. 

Contract terms  

The position is a temporary full-time employment for two years with the possibility of a one-year extension. 

The position requires physical presence throughout the entire employment. A valid residence permit must be presented by the start date, otherwise the offer may be withdrawn. 

What we offer 

• As a postdoc at Chalmers, you are an employee and enjoy all employee benefits. Read more about  working at Chalmers  and our benefits  for employees. 
• A dynamic and inspiring working environment in the coastal city of Gothenburg. 
• Read more about Sweden’s generous parental leave, subsidized day care, free schools, healthcare etc at Move To Gothenburg. 

Chalmers is dedicated to improving gender balance and actively works with equality projects, such as the GENIE Initiative for gender equality and excellence. 

If Swedish is not your native language, Chalmers offers Swedish courses to help you settle in. 

Application procedure 

The application should be written in English be attached as PDF-files, as below. Maximum size for each file is 40 MB. Please note that the system does not support Zip files. 

CV 

• A comprehensive CV, including a complete list of publications. 
• Details of previous teaching and pedagogical experience. 

Personal letter 

• A brief introduction about yourself. 
• A summary of your previous research fields and key research outcomes. 
• An outline of your future goals and research focus. 

Use the button at the foot of the page to reach the application form.  

Please note: The applicant is responsible for ensuring that the application is complete. Incomplete applications and applications sent by email will not be considered. Contact details to references will be requested after the interview. 

We welcome your application no later than April 30, 2026.