Post-Doc: Deep learning approaches to models of musical and environmental audio

National University of Singapore

We seek applicants with expertise in one or more of the following areas :

Qualifications: Successful candidates must have a PhD in Computer Science, Computer Engineering, Music Technology, or closely-related discipline by the date of appointment.

Responsibilities: Successful candidates will conduct research on building neural networks models for generating audio under parametric control and interaction. Activites will also include collecting and labeling data, bringing relevant literature to bear, writing code for deep learning models, and publishing work in leading jouranl and publication venues.

Context: A newly-funded 3-year program that includes PI's from Communications, Computer Science, and Electrical and Comptuer Engineering departments. The focus is on learning flexible generative sound models capable of realtime parmetric synthesis.

For this post-doctoral position, an emerging track record of quality research publications, ambitious research goals, strong coding skills, and some computational audio or musical experience would all be relevant.

Singapore is a modern, English-speaking city state that is connected to the world via global commerce, finance and transport networks with a stable climate year round and a cosmopolitan mix of cultures and languages.

Please submit the following documents by email:

  1. Full CV, including education, professional background, publoications, research activities and achievements, honours and awards, and accomplishments to date.
  2. A research statement (max. 3 pages) highlighting major accomplishments and short- and longer-term research plans, citing up to three significant publications, creative works or other scholarly contributions, and explaining their significance.
  3. Sample copies of research publications, if available.
  4. Pointers to any on-line material such as code or applications that are relevant.
  5. Four letters of reference (including one from the applicant's PhD or post-doctoral advisor/supervisor) to be arranged by the applicant to be submitted directly by the referees.

Email: lonce.wyse@nus.edu.sg
Lonce Wyse - Homepage
Posted August 12, 2019. Position open until filled.