ICASE PhD studentship: Music Data Science for Music Recommendation and Discovery

Supervised by Professor Mark Sandler, Centre for Digital Music; co-supervised by Dr Enzo Nicosia, School of Mathematical Sciences

This well-funded ICASE PhD (full UK fees plus tax-free stipend of nearly £20k) will investigate music discovery and recommendation for professional users, such as radio DJs and documentary producers, as well as for music consumers. The project is part of the on-going relationship between Queen Mary and the BBC including the Audio Research Partnership and the Data Science Research Partnership .

The successful candidate will study in the world-renowned Centre for Digital Music at Queen Mary and spend at least 1 month per year in BBC R&D Labs. The project is associated with the EPSRC-funded Programme Grant, Fusing Audio and Semantic Metadata for Intelligent Music Production and Consumption (see semanticaudio.ac.uk).

The research builds on a previous collaboration and extends it in several ways. The project will include many new musical audio features such as key, meter and instrumentation that are already under development in the Centre for Digital Music, and couple these so-called Content Derived Metadata (CDM) with other BBC metadata such as artist, genre and mood. The technical approach to be adopted will use Linked Data and Graph Theory, and enable CDM to be integrated into well-established collaborative filtering approaches to recommendation.

The project will include both scientific and technological development, as well as user studies with stakeholders from the BBC. The successful applicant should have a strong interest in music and sound, excellent programming skills and be capable of working with advanced mathematical concepts from Graph Theory and Linear Algebra. Understanding of DSP and Machine Learning is advantageous.

Candidates must have a first-class honours degree (or exceptionally, a high upper second) or equivalent, or a good MSc Degree in Computer Science, Electronic Engineering, Sound & Music Computing or equivalent. Experience in research and a track record of publications is very advantageous.

To apply, please follow the on-line process at (www.qmul.ac.uk/postgraduate/applyresearchdegrees/); click on the list of Research Degree Subjects, select ‘Electronic Engineering’ in the ‘A-Z list of research opportunities’, and follow the instructions on the right-hand side of the web page.

Please note that instead of the ‘Research Proposal’ we request a ‘Statement of Research Interests’. Your statement should answer the following questions: (i) Why are you interested in the topic? (ii) What relevant experience do you have? (iii) How you would begin your approach to the research? The statement should be brief: no more than 500 words or one side of A4 paper. In addition we would also like you to send a sample of your written work (e.g. excerpt of final year dissertation or published academic paper). More details can be found at: http://www.eecs.qmul.ac.uk/phd/how-to-apply

The closing date for applications is 31 March 2018, and interviews are expected to take place around the middle of April, with a start date as soon as possible and no later than 30 September 2018. Enquiries may be addressed to [Email Address Removed].