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[AUDITORY] musicology and data science PhD studentship available



Dear all

 

Following up on Josh's email about the DAME programme at QMUL: 

One of the proposed topics is focused on data science and musicology:

 

Predicting demographics, personalities, and global values from digital media behaviours. Digital platforms of media streaming, including radio and podcasts, TV and videos, offer access to behavioural signals that can be used to learn about the characteristics and preferences of individuals. The goal of the proposed research is to leverage the power of trails of digital media behaviours (most frequently listened to genres/artists, how often one listens to new music/artist suggestions, playlists, etc.). Such knowledge can then be employed to build (i) predictive models of complex high-level psychological constructs like moral and human values as well as on complex demographic attributes; (ii) multimodal personalised recommendation systems. The data informed models developed in this project will help unlock the potential of personalised, uniquely tailored user experiences, recommendation systems, and communication strategies in digital media—a strategic focus area of the UKRI-EPSRC portfolio—with applications in the creative industries and healthcare in particular (e.g., understanding well-being from musical choices). This project is in collaboration with Dr Kyriaki Kalimeri and the Data Science Lab at ISI Foundation (Turin, Italy; https://www.isi.it/en/home)

 

More information is available here: https://dame.qmul.ac.uk/ 


Best wishes

Charis


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Charalampos (Charis) Saitis
Lecturer (Assistant Professor), Digital Music Processing
 
Centre for Digital Music
School of Electronic Engineering and Computer Science
Faculty of Science and Engineering
Queen Mary University of London
10 Godward Square, Peter Landin Building, London E1 4FZ, UK
Tel: +44(0)20 7882 7518
Mob: +44(0)7717 619844
Email: c.saitis@xxxxxxxxxx  
www.c4dm.eecs.qmul.ac.uk

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We are always hearing, but are we listening? — Joel Chadabe