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 at the University of Oslo. 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.
PhD Research Fellowship in Machine Learning and Information Retrieval for Music-Related Movement
A PhD position 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 motion capture data of dance recordings, including feature extraction and selection, and matching against semantic descriptions of the data.
The research in the Robotic and Intelligent systems group is on machine learning strategies for a wide range of applications, including robotics, health care and music. Four permanent faculty members constitute the group, along with ten PhD students, five postdoctoral research fellows, and a lab engineer. The recruited candidate will be working within the recently awarded Centre of Excellence, Centre for Interdisciplinary Studies in Rhythm, Time and Motion (RITMO), alongside leading researchers from the Department of Informatics, Department of Musicology and the Department of Psychology at the University of Oslo.
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 1 April 2018.
The field of Music Information Retrieval (MIR) has developed advanced strategies for analysing music as an auditory phenomenon. Strategies involve feature extraction and selection based on physical properties of the sound signal and also models of human perception. Another important aspect of music, which to a lesser degree has been subject to MIR research, is movement: Music starts with sound-producing movement, and often also results in movement in the form of dance.
Movement may be quantified precisely using motion capture technology. But how are quantitative representations of movement related to semantic descriptions of the same movement? 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. The work involves contributing to data collection using state-of-the-art motion capture technology from Qualisys. Futher the candidate will use the collected motion capture data as training data for various machine learning tasks:
Automated generic post-processing techniques for motion capture data
(automatic marker recognition, gap-filling and marker swapping)
Classification of dance data based on semantic descriptions
(such as dance genre/style, gender, expressivity, etc.)
Explore deep learning techniques for automated synthesis of dance movement.
Requirements and qualifications:
The Faculty of Mathematics and Natural Sciences has a strategic ambition of being a leading research faculty. Candidates for this fellowship will be selected in accordance with this, and expected to be in the upper segment of their class with respect to academic credentials.
Applicants must have a Master’s degree in a relevant field such as computer science, machine learning, biokinematics or musicology/music information retrieval. A solid background in computer science and machine learning is required, as well as good analytical and programming skills. Experience with Matlab and MIRtoolbox/MoCap toolbox is preferable. Further, competence in several of the following fields is desired and will be considered an advantage when candidates are ranked: data analysis, digital signal processing, motion capture technology and music.
Candidates without a Master’s degree have until 31.01.2018 to receive their degree.
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:
Pay grade: NOK 436 900 - 490 900 per year, depending on qualifications and seniority.
- A stimulating working environment within the RITMO centre of excellence
- Attractive welfare benefits
The application must include:
- Application letter, including a summary of research interests, and a brief description of how your Master's thesis work and other experience is relevant for the position.
- CV (summarizing education, positions and academic work - scientific publications)
- Copies of educational certificates, transcript of records and letters of recommendation
- The most relevant and important publications and academic work that the applicant wishes to be considered by the evaluation committee (maximum 5)
- Documentation of English proficiency
- Names and contact details of 2-3 references (name, relation to candidate, e-mail and telephone number)
Foreign applicants are advised to attach an explanation of their University’s grading system. Please remember that all documents should be in English or a Scandinavian language.
In accordance with the University of Oslo’s equal opportunities policy, we invite applications from all interested individuals regardless of gender or ethnicity.
The University of Oslo has an Acquisition of Rights Agreement for the purpose of securing rights to intellectual property created by its employees, including research results
Associate Professor Kristian Nymoen, +47 22841693, firstname.lastname@example.org
For questions about the recruitment system, please contact HR Officer Helene Jansen +47 22857196, email@example.com
- Søknadsfrist31. oktober 2017
- ArbeidsgiverUniversity of Oslo
- Intern-ID2017/10595 - 1017
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