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PhD Research Fellow in Cloud-based Skill Learning and Transfer for Soft Collaborative Robots

Deadline: 16.09.2020

Western Norway University of Applied Sciences

With about 16,000 students, Western Norway University of Applied Sciences is one of the largest higher education institutions in Norway. A broad range of academic programmes are offered at Bachelor, Master and PhD levels, spread out on five campuses Førde, Sogndal, Bergen, Stord og Haugesund.

Our ambition is to build stronger and more solid academic and research environments that will interact nationally and internationally. The aim is to become a recognized actor on the international higher education arena. Increased international cooperation and engagement in externally funded projects will work towards this goal.

The Faculty of Engineering and Science has about 270 employees and about 3200 students. The faculty has a wide range of educational programs at both bachelor and master levels in engineering and science, as well as PhD education in computer technology. Mohncenter for Innovation and Regional Development researches innovation and offers master programs in innovation and entrepreneurship. Diving education offers one-year vocational education.

The majority of the faculty's activities are in Haugesund, Bergen, Sogndal and Førde, but we also offer decentralized education in Florø, Kristiansund and at Stord. The faculty's activities are internationally established and work in close collaboration with regional companies, clusters, health care companies and the public sector, including other institutions in the university and college sectors. This applies to research, development, innovation and not least education with student projects at all levels.

PhD Research Fellow in Cloud-based Skill Learning and Transfer for Soft Collaborative Robots

The Department of Computer Science, Electrical Engineering and Mathematical Sciences at Western Norway University of Applied Sciences, has a vacancy for a research fellow (PhD position) in Cloud-based Skill Learning and Transfer for Soft Collaborative Robots for a period of 4 years. The Research Fellow will be part of HVL Robotics, an emerging centre for robotics research and innovation in Western Norway with strong industrial ties. The candidate will work closely with 3 existing PhD students in the same laboratory.

The PhD research fellow will be part of the PhD programme in Computer Science: Software Engineering, Sensor Networks and Engineering Computing (https://ict.hvl.no). The research programme in Computer Science currently includes 20 professors and associate professors, more than 30 PhD and post-doctoral fellows, and a large number of master’s students.

About the PhD project/ work tasks:

The research topic to be addressed in the PhD project is related to robot Learning from Demonstration (LfD) on an industry-relevant task (e.g. collaborative part assembly) with a soft and sensor-driven collaborative robot. In particular, how this can be combined with self-exploration of the learned skill model, exploiting the soft robot’s ability to gently explore its environment, but with strict constraints on safety and task failure. And, how effective skill transfer can be demonstrated on such a task, across two similar robots with soft components (in the robot hand, and/or in the joints), through a combination of teacher demonstrations and self-learning.

The supervision team is led by Associate Professor Martin F. Stølen, with co-supervision from Associate Professor Erik Kyrkjebø and Professor Knut Øvsthus at HVL, and Senior Lecturer Matthew Howard at King’s College London.

Research environment:

The computer science research environment at Western Norway University of Applied Sciences has a strong focus on use-inspired and applied research, and on ICT as an enabling technology. The research environment has cooperation with many national and international research groups, and with national and regional industry partners. The research programme includes the research themes of software engineering, engineering computing, sensor networks and measurement technologies, grid computing and physics data analysis, machine learning, and interactive and collaborative systems. The prospective PhD candidate will work in close cooperation with our current PhD students in the intersection of collaborative robotics and machine learning.

PhD research fellows receive an annual work expense funding which can be used for conference participation, research visits, and equipment. The place of employment is Campus Førde.


The PhD research fellow must hold a master's degree in computer science or in a closely related field, combined with some previous experience on software and/or machine learning applied to robotics. Or alternatively, a master’s degree in robotics or artificial intelligence, with a strong emphasis on computing aspects. Candidates who have submitted a master’s thesis (but who has not yet been awarded a master’s degree) may also qualify for the position provided that the master`s degree is awarded within 4 weeks after the application deadline. A solid background in robotics and control, learning strategies (reinforcement learning, LfD), and/or soft robotics, will be considered an advantage when candidates are ranked. Candidates already holding a PhD within this field are not eligible for this position.

In addition to the required educational and scientific background, the following criteria will be evaluated: competence and grades on completed course work, quality of the master's thesis (excellent grade, equivalent of grade B or better on the ECTS grading system), publications (if any), research and teaching experience, practical software engineering skills and experience. A possible outline of a research plan for a potential PhD project will also be taken into account.

The candidate must be diligent and display the ability to work independently, supplemented with regular guidance, and is expected to carry out high-quality research and to publish the results in international workshops, conferences, and journals.

The PhD research fellow must enroll in the PhD programme in Computer Science: Software Engineering, Sensor Networks and Engineering Computing at Western Norway University of Applied Sciences, and must meet the formal admission requirements for admission into the PhD programme. 25% of the 4-year period will be designated to duties such as teaching, development and administrative tasks. The employment period may be reduced if the successful applicant has held previous employment as a research fellow.

An application for enrolment should first be submitted after an appointment is made and the supervisor(s) will help with this procedure. The candidate must be enrolled as a PhD student within 3 months from the start of the employment.

Application procedure:

Applications will be evaluated by an expert panel of three members.

Applicants are asked to submit their application and CV online. Please use the link “Apply for this job” (“Søk stillingen”).

The following documentation should be uploaded as an attachment to the online application:

  • Master Thesis
  • Copies of selected academic publications (no more than 15)
  • A CV with a complete list of academic publications
  • Diplomas and certificates

Applicants should indicate which publications or parts of publications should be given special consideration in the evaluation. If the documents submitted are not in a Scandinavian language or in English, the applicants must submit certified translations of these. The transcripts must specify the topics, the course works, and the grades at the bachelor`s and master`s degree levels.

Applicant whose education is from another country than Norway, need to also attach a certified translation of the diploma and transcript of grades to English or a Scandinavian language, if the original is not in any of these languages. It is required that the applicant enclose a review from NOKUT whether the education (bachelor and master’s degree) is of a scope and level that corresponds to the level of a Norwegian master’s degree. Please see www.nokut.no/en for more information about NOKUT’s general recognition. This may take some time and we recommend you to apply as soon as you know you will apply for this position. If no answer within the application deadline, please enclose documentation from NOKUT that they have received your application.

Applicants should note that the evaluation will be based on the documentation submitted electronically via Jobbnorge within the submission deadline. The applicants are responsible for ensuring that all the documentation is submitted before the closing date. It is of utmost importance that all publications to be considered in the evaluation are uploaded as an attachment with the application, since these are sent electronically to the expert panel. Applications cannot be sent by e-mail or to individuals at the college.


  • Good occupational pension, insurance and loan schemes from The Norwegian Public Service Pension Fund
  • Exciting academic environment with the possibility of competence enhancement and development
  • Opportunities for training within the working hours

Initial salaries will be offered at grade 54 (code 1017) in the Civil Service pay grade table scale.

There is a compulsory 2 % deduction to the pension fund (see http://www.spk.no for more information). The successful applicant must comply with the guidelines that apply to the position at any time.

General information:

The appointment will be made in accordance with the regulations for State employees Law in Norway ("Lov om statens ansatte)". Organizational changes and changes in the duties and responsibilities associated with the position must be expected.

State employment shall reflect the multiplicity of the population at large to the highest possible degree. Western Norway University of Applied Sciences Bergen has therefore adopted a personnel policy objective to ensure that we achieve a balanced age and gender composition and the recruitment of persons of various ethnic backgrounds.

Information about the applicant may be made public even though the applicant has requested not to be named in the list of applicants. The applicant will be notified if his/her request is not respected.

Short-listed applicants will be called in for an interview and a presentation of previous work, e.g. based on their master’s thesis.


1) Associate Professor Martin F. Stoelen (Stølen), phone: +47 95 48 17 12, e-mail: [email protected]

2) Professor Håvard Helstrup, Coordinator of PhD Programme on Computer Science, phone: (+47) 55 58 75 61, e-mail: [email protected]

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