Research Fellow, Yong Siew Toh Conservatory of Music
- NATIONAL UNIVERSITY OF SINGAPORE
- 31 Mar 2023
- End of advertisement period
- 01 May 2023
- Academic Discipline
- Engineering & Technology, Computer Science, Social Sciences, Communication & Media Studies, Psychology
- Job Type
- Academic Posts, Research Fellowships
- Contract Type
- Fixed Term
- Full Time
The Yong Siew Toh Conservatory of Music, National University of Singapore, offers a unique and adventurous 21st century Asian environment in which we train and educate performers, composers and recording engineers to take advantage of future professional and artistic opportunities both in Singapore and in the world. The Conservatory is distinctively international in terms of its faculty, student population and artistic outlook. Our mission is to be a focal point for musical activity, artistic development and research, both for Singapore and the Asia-Pacific region.
The Conservatory is seeking a full-time Postdoctoral Research Fellow in Musical Brain Computer Interface technology.
The Research Fellow (RF) will design studies and conduct research testing the efficacy of a newly-developed music-based Brain Computer Interface (BCI) for emotion regulation in listeners. She/he will work in a multi-disciplinary team to 1) conduct R&D of our automatic music generation systems for affective music generation, and 2) help test the efficacy of a music generation system paired with a BCI for emotion regulation in healthy as well as neurological and/or mental health patients. The RF will design and conduct experimental research and user studies, help coordinate research activities, and perform data analyses. The RF will need to be capable of working both independently and in a team, of developing innovative solutions, and of publishing research findings in high-impact conferences and journals. This position is part of an exciting large-scale (multi-research team) project that aims to create a holistic BCI solution for the restoration and enhancement of brain functions.
- Design and develop user studies and experiment interfaces to test the efficacy of an affective music generation system paired with a BCI.
- Explore solutions for music and BCI-driven therapy for mental health (depression, anxiety).
- Conduct pilot trials of an EEG-based musical BCI
- Conduct data analysis, perform statistics, and interpret the users’ behavioral and neural signals.
- Prepare manuscripts and publish in high-impact journals and conferences.
- Assist in supervising research staff and students.
- Participate in IRB applications and report writing.
- If candidate’s background allows: Co-develop novel algorithms for our BCI system for emotion regulation, modify code for automatic music generation algorithms for greater efficacy.
- Ph.D. in Cognitive Science, Computer Science & Engineering, Music Information Retrieval (MIR), Psychology, or related disciplines
- Significant experience with experimental design, quantitative analysis, and statistics
- Strong publication track record
- Programming experience
- Ability to work independently and in teams
- Some knowledge of music / music theory is strongly desired
- Computational neuroscience and neuroimaging (e.g., EEG) experience a strong plus
- Experience with algorithmic music or automatic music generation is advantageous
Duration and other details:
- Position available immediately
- 1 year contract, with possible extension up to an additional 6 months
- Competitive salary and benefits
- The candidate must be based in, or be able to relocate to, Singapore (working from abroad is not possible due to rules of the funding body)
To apply, please include a cover letter, outlining your background and interest in the position, sharing why you would be a good fit for this role. Please also submit your curriculum vitae, names and contact information for 3 references.
Enquiries about the position can be sent to Asst Prof Kathleen Agres at email@example.com.
For best consideration, applications should be received by 1 May 2023.
Location: Kent Ridge Campus
Organization: Yong Siew Toh Conservatory of Music
Department : Dean's Office (YST Conservatory of Music)
Employee Referral Eligible: No
Job requisition ID : 19753