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

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. The position is 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. 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)

A prerequisite for employment is that the candidate is to be admitted 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 

More about working at UiA. 

The position is remunerated according to the State Salary Scale, alary 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.

General information

UiA is an open and inclusive university. We believe that diversity enriches the workplace and makes us better. We, therefore, encourage qualified candidates to apply for the position independent of gender, age, cultural background, disability or an incomplete CV.

Women are strongly encouraged to apply for the position. 

The successful applicant will have rights and obligations in accordance with the current regulations for the position, and organisational changes and changes in the duties and responsibilities of the position must be expected. The engagement is to be made in accordance with the regulations in force concerning the acts relating to Control of Export of Strategic Goods, Services and Technology.  

Appointment is made by the University of Agder’s Appointments Committee for Teaching and Research Positions. A background check may be conducted to verify information that appears in available documents. Background checks are always done with the applicant's consent, and employment in the position requires an approved background check. Relevant applicants will receive further information. 

 Short-listed applicants will be invited for interview. With the applicant’s permission, UiA will also conduct a reference check before appointment. Read more about the employment process. 

 In accordance with the Freedom of Information Act § 25 (2), applicants may request that they are not identified in the open list of applicants. The University, however, reserves the right to publish the names of applicants. Applicants will be advised of the University’s intention to exercise this right.

Application

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

The applicant is fully responsible for submitting complete digital documentation before the closing date. All documentation must be available in a Scandinavian language or English.

Application deadline: 28.10.26.

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

Creating knowledge together

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The University of Agder combines the unique warmth and charm of Southern Norway with first-class scientific, technological and artistic expertise.

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