PhD Research Fellowship in machine learning and information retrieval for music-related movement University of Oslo, Department of Informatics Norway

PhD Research Fellowship in machine learning and information retrieval for music-related movement

Job description

A Doctoral Research Fellowship is available within the Robotics and Intelligent Systems group (ROBIN) at the Department of Informatics, University of Oslo. The main area of focus within the position is automated classification of full body motion capture data, including automating techniques for post-processing and matching against semantic descriptions of the data.

The recruited candidate will be working at the RITMO Centre for Interdisciplinary Studies in Rhythm, Time and Motion with leading researchers in Informatics, Musicology and Psychology. It is expected that all members of the center contribute to the general activities and collaborations within RITMO. The researchers have access to state-of-the-art facilities in sound/video recording, motion capture, eye tracking, physiological measurements, various types of brain imaging (EEG, fMRI), and rapid prototyping and robotics laboratories.

The appointment is for a period of 3 years. There might be a possibility to extend to 4 years depending on the qualifications of the recruited candidate, and the department’s need for teaching and lab assistants.

Suggested starting date is 1 September 2018; the starting date can under no circumstances be later than 1 October 2018.


More about the position


Body motion is an important component of human communication. Ranging from everyday communication and body language to artistic expressions in dance body motion may express meaning, intention and emotional state. We are able to recognise information of various complexity such as gait style, gender or emotion, even from heavily reduced displays of body motion, such as point-light displays based on motion capture data.

This project researches machine learning techniques for full body motion capture recordings of dance movement. Some central questions in the research project are: How are semantic descriptions of dance movement reflected in quantitative representations with motion capture data? Can a computer be trained to classify dance styles and dance genres? And is it possible for a computer or a robot to imitate human dance movement from audio?


In the announced project, the recruited PhD candidate will research machine learning techniques for full-body motion capture data, including:

1. Automated generic post-processing techniques for motion capture data
(automatic marker recognition and prediction of missing marker locations).

2. Automated classification dance styles from full body motion capture data.

3. Explore deep learning techniques for automated synthesis of dance movement.

The recruited candidate will also contribute to data collection of in the RITMO motion capture lab, which is equipped with state-of-the-art motion capture technology from Qualisys.


Qualification requirements


 The Faculty of Mathematics and Natural Sciences has a strategic ambition of being a leading research faculty. Candidates for these fellowships will be selected in accordance with this, and expected to be in the upper segment of their class with respect to academic credentials.

  • A Master’s degree in a relevant field such as computer science, machine learning, biokinematics or music information retrieval. The applicant is required to document that the degree corresponds to the profile for the post.
    • the average grade point for courses included in the Master’s degree must be B or better in the Norwegian educational system
    • the Master’s thesis must have the grade B or better in the Norwegian educational system
    • the average grade point for courses included in the Bachelor’s degree must be C or better in the Norwegian educational system
  • A solid background in computer science and machine learning.
  • Competence in one or more of the following fields: deep learning, motion capture technology, biokinematics, data analysis, digital signal processing, and music.
  • Personal suitability and motivation for the position.

All Ph.D. candidates must demonstrate high English language skills. International applicants must document these skills prior to admission to the PhD programme by passing one of the following tests with these or better grades:

  • TOEFL – Test of English as Foreign Language, internet based test (IBT). Minimum total score: 80
  • IELTS – International English Language Testing Service. Minimum overall band score: 6.5
  • Certificate in Advanced English (CAE) and Certificate of Proficiency in English (CPE) from the University of Cambridge
  • PTE Academic – Pearson Test of English Academic. Minimum overall score: 62
  • Please see here for exemptions to the English requirements.
  • Please see here for exemptions to the English requirements.

Candidates without a Master's degree have until 30 June, 2018 to complete the final exam. 

The purpose of the fellowship is research training leading to the successful completion of a PhD degree.

The fellowship requires admission to the PhD programme at the Faculty of Mathematics and Natural Sciences. The application to the PhD programme must be submitted to the department no later than two months after taking up the position. For more information see:

Application and admission to the PhD programme in natural sciences


We offer

  • Salary NOK 436 900 – 490 900 per year depending on qualifications and seniority as PhD Research Fellow, (position code 1017)
  • A professionally stimulating working environment
  • Attractive welfare benefits
  • membership in the Norwegian Public Service Pension Fund


How to apply


Applicants must submit the following attachments with the electronic application, preferably in PDF format:

  • Application letter describing qualifications for the announced research project and the applicant’s motivation for the position.
  • Curriculum Vitae (complete list of education, positions, teaching experience, administrative experience and other qualifying activities, including a complete list of publications with links to full version of published papers)
  • Copies of educational certificates and transcript of records. Applicants with education from a foreign university are advised to attach an explanation of their university's grading system.
  • Documentation of English proficiency
  • Names and contact details of 2-3 references (name, relation to candidate, e-mail and telephone number)

Short-listed candidates may be invited to an interview at the University of Oslo or we will arrange for a video-based interview.


Formal regulations

No one can be appointed for more than one PhD Research Fellowship period at the University of Oslo.


Please see the guidelines and regulations for appointments to Research Fellowships at the University of Oslo.


According to the Norwegian Freedom and Information Act (Offentleglova) information about the applicant may be included in the public applicant list, also in cases where the applicant has requested non-disclosure.


The appointment may be shortened/given a more limited scope within the framework of the applicable guidelines on account of any previous employment in academic positions.


The University of Oslo has an agreement for all employees, aiming to secure rights to research results etc.


Contact information

Associate Professor Kristian Nymoen, +47 22841693,


For technical questions about the recruitment system, please contact HR Officer Helene Jansen, +47 22857196,


About the University of Oslo

The University of Oslo is Norway’s oldest and highest rated institution of research and education with 28 000 students and 7000 employees. Its broad range of academic disciplines and internationally esteemed research communities make UiO an important contributor to society.


The Department of Informatics (IFI) is one of nine departments belonging to the Faculty of Mathematics and Natural


Sciences.. IFI is Norway’s largest university department for general education and research in Computer Science and related topics. The Department has near 950 students on bachelor level, near 450 master students, and over 180 PhD students. The overall staff of the Department is close to 250 employees, about 200 of these are full time positions. The full time scientific staff is 60, mostly Full/Associate Professors.



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