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Doctoral student in Interpretable and Experience-Driven Learning for Collaborative Robots
Chalmers University of Technology

Doctoral student in Interpretable and Experience-Driven Learning for Collaborative Robots

2026-06-30 (Europe/Stockholm)
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Om arbejdsgiveren

Our goal is to focus on competence, knowledge and collaboration in order to play an important, demonstrable role in social development.

Besøg arbejdsgiverens side

We are looking for a highly motivated doctoral student to pursue a PhD at the intersection of Interpretable Artificial Intelligence, experience-based learning, and Human-Robot Collaboration (HRC).

Join us to take collaborative robots the extra MILE by developing interpretable, experience-driven AI that helps robots learn, adapt, and collaborate safely with people. 

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.

The Division of Systems and Control conducts interdisciplinary research in automatic control, automation, and mechatronics, in close collaboration with industry and society. The division hosts the SAFER research centre and the Revere laboratory, with research focused on areas such as energy efficiency, sustainable battery use, smart automation, and autonomous vehicles.

About the research project  

Collaborative robots are increasingly expected to work alongside people in shared, dynamic environments, but they still struggle to understand human intentions, adapt to changing situations, and explain their actions. This PhD position will address these challenges by developing interpretable AI and robot learning methods that connect human-aware reasoning with adaptive robot behaviour.

The position is part of the project MILE-Cobots: Multidimensional Interpretable Learning for Experience-Driven Collaborative Robots, funded by the Swedish Research Council (Vetenskapsrådet). 

Who we are looking for

The following requirements are mandatory:

  • To qualify as a Doctoral student, you must have a Master's degree equivalent to at least 240 higher education credits in Electrical Engineering, Computer Science, Robotics, Applied Mathematics, or a similar field. 
  • A solid background in machine learning methods applied to robotics, robot learning, interpretable AI, or autonomous systems. 
  • Good programming skills, preferably including C++ and Python, and experience with ROS (Robot Operating System). 
  • A genuine interest in collaborative robotics, interpretable AI, human-robot interaction, and adaptive robot behaviour.  
  • Strong written and verbal communication skills in English. 

The following experience will strengthen your application: 

  • Experience with Unity or simulation environments such as Gazebo, MuJoCo, Isaac Sim, or similar. 
  • Demonstrated experience applying AI methods on robotic platforms, for example, through research projects, GitHub/GitLab repositories, or other documented implementations.
  • Knowledge of robot planning, control, human intention recognition, explainable AI, human-robot collaboration, or knowledge representations. 
  • Experience with interdisciplinary teamwork and international collaboration.
  • International exchange or research experience. 
  • Teaching experience,  e.g., as a Teaching Assistant (TA) or Lecturer. 
  • Peer-reviewed publication(s), especially as first author.

What you will do

  • Pursue independent research in interpretable AI and human-robot collaboration, while developing your own scientific ideas and expanding your expertise within the areas covered by the project.
  • Take advanced-level courses within the Graduate School of Electrical Engineering.
  • Design and develop interpretable learning frameworks that enable collaborative robots to understand, plan, adapt, and explain their actions in dynamic, multi-agent environments. 
  • Develop AI models for representing collaborative task structures, including actions, tasks, goals, and role allocation between humans and robots.
  • Develop experience-based learning and memory methods that allow robots to learn from previous successes and failures.
  • Implement and validate your methods in simulation environments and on real robotic platforms, such as a fixed-frame collaborative robot and a mobile manipulator.
  • Present your research at national and international academic conferences.
  • Contribute to advancing state-of-the-art methods and publish your results in peer-reviewed journals.
  • Collaborate with team members, external academic partners, and industry collaborators in an inclusive and interdisciplinary research environment.

 This is a full-time position, limited to a maximum of five years.

 Contract terms  

  • The Doctoral student positions are fully funded from the start. 
  • The position is a fixed-term appointment of four years, with the possibility to teach up to 20%, which extends the position up to five years. 
  • A starting salary of 35,725 SEK per month (valid from May 1, 2026). 
  • Doctoral studies require physical presence throughout the entire study period. A valid residence permit must be presented by the study start date; otherwise, the admission may be withdrawn. 

What we offer 

  • As a Doctoral student 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.

Find more general information about doctoral studies at Chalmers here.  

Application procedure 

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

CV 

Personal letter (1 page)

The letter should include:

  • A brief introduction about yourself. 
  • A brief motivation as to why you are interested in this position. 

Bachelor’s and, if available, master’s thesis together with the transcripts. 

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

A background check may be conducted as part of the application process.

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 for references will be requested after the interview. 

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

For questions, please contact:  

Karinne Ramirez-Amaro 
Associate Professor 
[email protected] 

We look forward to your application! 

*** Chalmers declines to consider all offers of further announcement publishing or other types of support for the recruiting process in connection with this position. ***  

 Chalmers University of Technology in Gothenburg conducts research and education in technology and natural sciences at a high international level. The university has 3100 employees and 10,000 students, and offers education in engineering, science, shipping and architecture. With scientific excellence as a basis, Chalmers promotes knowledge and technical solutions for a sustainable world. Through global commitment and entrepreneurship, we foster an innovative spirit, in close collaboration with wider society. 
Chalmers was founded in 1829 and has the same motto today as it did then: Avancez – forward.

Jobbeskrivelse

Titel
Doctoral student in Interpretable and Experience-Driven Learning for Collaborative Robots
Beliggenhed
Maskingränd 2 Göteborg, Sverige
Publiceret
2026-05-27
Ansøgningsfrist
2026-06-30 23:59 (Europe/Stockholm)
2026-06-30 23:59 (CET)
Jobtype
Gem job

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Om arbejdsgiveren

Our goal is to focus on competence, knowledge and collaboration in order to play an important, demonstrable role in social development.

Besøg arbejdsgiverens side

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