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

About the Position

A fixed-term 100% position as a PhD Research Fellow in Mechatronics is available at the University of Agder, Faculty of Engineering and Science, affiliated with the Department of Engineering Sciences. The position is for a period of three years, located at Campus Grimstad. The starting date is negotiated with the faculty.

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. The position is connected to the disciplinary field of Mechatronics and the research group of Robotics and Automation.

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.
• General grade requirements:
• Average grade for all courses in the master's degree should be B (or equivalent) or higher.
• Master's thesis should have a grade B (or equivalent) or higher.
• Average grade for courses in the bachelor's degree should be C (or equivalent) or higher.
• English language requirement (if not exempt per NOKUT guidelines):
• TOEFL: minimum 600 for Paper-based Test (PBT), or 92 for Internet-based Test (iBT).
• IELTS: minimum 6.5.
• A prerequisite for employment is admission to UiA's PhD programme at the Faculty of Engineering and Science.

Desired Qualifications

• Experience with research and scientific publications.
• Strong background in control, robotics and machine learning, and experience in areas like model predictive control, adaptive control, reinforcement learning, robot perception or manipulation.
• Programming in Matlab, Python, C/C++, Robot operating system (ROS).

Personal Qualities

Personal suitability and good teamwork skills will be emphasized in the evaluation as well as relevant practical experience. Research Fellows are expected to contribute to the active research community at the University. The position places demand on the applicant's capacity for independent goal-oriented work, ability to concentrate and attention to detail.

We Offer

• Professional development in a large, exciting and socially influential organisation.
• A positive, inclusive and diverse working environment.
• Modern facilities and comprehensive welfare schemes.
• Membership in the Norwegian Public Service Pension Fund.
• The position is remunerated according to the State Salary Scale, salary plan 17.515, code 1017 PhD Research Fellow, NOK 550,800 gross salary per year. A compulsory pension contribution to the Norwegian Public Service Pension Fund is deducted from the pay according to current statutory provisions.

Application Requirements

Applications, including documentation of education and experience (such as diplomas and certificates), must be submitted electronically via the link "Apply for this job". The following documentation must be uploaded electronically:

• Transcripts and diplomas for master's and bachelor's studies with grades.
• Summary of the Master Thesis (maximum 2 pages).
• CV with detailed education, work experience, and a list of scientific publications.
• A letter of motivation and brief project description related to the research topic described above (maximum 2 pages).
• Up to 5 academic articles that the candidate wishes to emphasize in the assessment process.
• Names and contact information of 2 referees.
• All documentation must be available in a Scandinavian language or English.

Application dates

Milestone	Date
Application deadline	28 October 2026
Starting date	Negotiated with faculty

Contact

• For questions about the position: Professor Jing Zhou, tel. +47 37 23 31 91, e-mail jing.zhou@uia.no
• For questions about the application process: HR-advisor Heidi Kristensen, tel. +47 38 14 13 79, e-mail heidi.kristensen@uia.no

Official Link

https://www.jobbnorge.no/en/available-jobs/job/308334/phd-research-fellow-in-learning-based-control-of-autonomous-robot-manipulation

Important Notes

• Women are strongly encouraged to apply.
• UiA is an open and inclusive university that encourages qualified candidates to apply independent of gender, age, cultural background, disability or an incomplete CV.
• A background check may be conducted with the applicant's consent.
• The engagement is made in accordance with regulations concerning the Control of Export of Strategic Goods, Services and Technology.

How to Apply

Submit your application through the official portal before the deadline: 28 October 2026. Read the eligibility requirements carefully and prepare all requested documents — early applications are strongly recommended for competitive awards.

Open the official application page ↗

Application guides

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