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Karinne Ramirez-Amaro

4 months ago

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

Degree Level

PhD

Field of study

Computer Science

Funding

Available

Deadline

Expired

Country flag

Country

Sweden

University

Chalmers University of Technology

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Keywords

Computer Science
Machine Learning
Electrical Engineering
Artificial Intelligence
Reinforcement Learning
Collaborative Robotics
Experiential Learning
Robotics
Explainability
Autonomous System
Mechatronics
Control System

About this position

Chalmers University of Technology invites applications for a fully funded PhD position in Interpretable and Experience-Driven Learning for Collaborative Robots. This opportunity is based in the Division of Systems and Control within the Department of Electrical Engineering, renowned for its interdisciplinary research in automation, mechatronics, and control systems. The research project, MILE-Cobots, aims to advance collaborative robots by developing interpretable AI and experience-based learning methods that enable robots to understand, adapt, and safely collaborate with humans in dynamic environments.

The successful candidate will join a vibrant research community, working closely with academic and industry partners. The project focuses on human-aware reasoning, adaptive robot behaviour, and interpretable learning frameworks. You will design and develop AI models for collaborative task structures, implement experience-based learning and memory methods, and validate your approaches in both simulation environments and real robotic platforms. The position offers opportunities to present research at international conferences and publish in peer-reviewed journals.

Applicants must hold a Master's degree (or equivalent, at least 240 higher education credits) in Electrical Engineering, Computer Science, Robotics, Applied Mathematics, or a related field. Essential qualifications include a strong background in machine learning applied to robotics, robot learning, interpretable AI, or autonomous systems, as well as programming skills in C++ and Python and experience with ROS. Additional experience with simulation environments (Unity, Gazebo, MuJoCo, Isaac Sim), robot planning, control, human intention recognition, explainable AI, and interdisciplinary teamwork will strengthen your application. International research experience, teaching, and peer-reviewed publications are advantageous. Physical presence in Sweden is required throughout the study period, and a valid residence permit must be presented by the start date.

The position is fully funded, with a starting salary of 35,725 SEK per month (from May 1, 2026), and includes full employee benefits. The appointment is for four years, with the possibility to teach up to 20%, extending the position to five years. Chalmers offers a dynamic working environment in Gothenburg, with generous parental leave, subsidized day care, free schools, and healthcare. The university is committed to gender equality and excellence, and offers Swedish language courses for international students.

To apply, submit your CV, personal letter, and thesis transcripts as PDF files via the online application form. Applications must be written in English and submitted by June 30, 2026. Incomplete applications and those sent by email will not be considered. References will be requested after the interview. For questions, contact Associate Professor Karinne Ramirez-Amaro at [email protected].

Funding details

Available

What's required

Applicants 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 is required. Good programming skills, preferably including C++ and Python, and experience with ROS (Robot Operating System) are mandatory. Strong written and verbal communication skills in English are essential. Experience with simulation environments (Unity, Gazebo, MuJoCo, Isaac Sim), applying AI methods on robotic platforms, robot planning, control, human intention recognition, explainable AI, human-robot collaboration, or knowledge representations will strengthen the application. Interdisciplinary teamwork, international collaboration, teaching experience, and peer-reviewed publications are advantageous. Physical presence in Sweden is required throughout the study period, and a valid residence permit must be presented by the study start date.

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Professors

Associate Professor at Chalmers University of Technology

University Name
Country flag

Sweden

Research Interests

Human-robot Interaction

Artificial Intelligence

Causal Inference

Reinforcement Learning

Mobile Robotics