PhD Research Fellow in Learning-based Control of Autonomous Robot Manipulation

The Department of Engineering Sciences has more than 90 employees in scientific positions and more than 1500 students at all levels. A wide range of research activities is conducted across the department’s research groups: Mechatronics, Renewable Energy, Civil Engineering, and Industrial Economy. Interdisciplinary projects within the department or with other research groups are also welcome. 

The position is connected to the disciplinary field of Mechatronics and the research group of Robotics and Automation. The Robotics and Automation research group has substantial and on-going experience of leading and contributing to research projects funded by the Research Council of Norway, the Norwegian Directorate for Higher Education and Skills (HK-Dir), the EU, and others. 

Responsibilities

Project Description

In this position, you will explore how learning-based control (data-driven control), machine learning algorithms, and perception methods can improve the autonomy, robustness, and precision of robotic manipulation in challenging environments. The project lies at the intersection of control theory, reinforcement learning, robotics and perception. You will investigate new algorithms and methods for robust and adaptive manipulation, including learning-based control for robotic systems and advanced visual perception methods for reliable object detection, scene understanding, and interaction under adverse environment conditions. The goal is to enable fully autonomous execution of complex manipulation tasks, such as for offshore exploration, maintenance, and repair. You will test and validate methods on real robotic platforms at Motion Lab. You will have opportunities for research visits to collaborated universities in Japan, Canada, and USA, under the UTFORSK NCUJ-SCORE project.

The research will include the preparation, drafting and submission of research reports, publication of high-quality scientific articles, and participation in dissemination activities at the European level.

Required qualifications

• Applicants must hold a master’s degree in mechatronics, control systems, robotics, or a closely related field obtained within the last five years.
• Applicants should have expertise in one of the following fields: advanced control theory, robotics, mechatronics. Additional training in machine learning methods is an advantage.

As a general rule, the following should apply:

• The average grade for all courses in the master’s degree should be B (or equivalent) or higher. 
• The master's thesis (or equivalent) should have a grade B (or equivalent) or higher. 
• The average grade for courses included in the bachelor's degree (or equivalent) should be C (or equivalent) or higher. 
• Competence in English is a requirement for all applicants to the PhD program. International candidates that are not exempt from the English language requirements pursuant to the guidelines of the Norwegian Agency for Quality Assurance in Education (NOKUT), must document this through one of the following tests with the stated results or better: 
• TOEFL - Test of English as a Foreign Language with a minimum score of 600 for the Paper based Test (PBT), or 92 for the Internet based Test (iBT)
• IELTS - International English Language Testing System, with the result of 6.5

Criteria for positions as PhD Research Fellow (in Norwegian)