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[AUDITORY] Funded PhD in Machine Listening / Music Informatics at Queen Mary University of London



Dear all,

A funded PhD place in the fields of machine listening / music informatics is available at the Centre for Digital Music, Queen Mary University of London.
Full details below, or at http://www.jobs.ac.uk/job/AMT233/ .

Best,
Emmanouil Benetos



Funded PhD studentship in Machine Listening / Music Informatics at the Centre for Digital Music, Queen Mary University of London


Applications are invited from all nationalities for a funded PhD Studentship starting Autumn 2016 within the Centre for Digital Music (C4DM) in the fields of machine listening / music informatics.

RESEARCH PROJECT: PhD applications are invited that address one of the following topics:
- Recognition and Separation of Musical Instruments in Polyphonic Audio: The goal of this project is to develop computational techniques for automatic identification/separation of multiple instruments in music signals, as well as instrument assignment – i.e. assigning detected notes to a specific instrument.
- Sound Event Detection in Multisource Environments: This project will focus on detecting sound events from everyday acoustic scenes. The successful candidate will research and develop computational methods suitable for detecting overlapping acoustic events in noisy and complex environments.
- Music Language Models for Audio Analysis: The goal of this project is to develop language models for polyphonic music and integrate them to systems for analysing music signals (e.g. automatic music transcription, chord estimation), in a similar way that spoken language models are combined with acoustic models for automatic speech recognition.

SKILLS: Candidates must have a first-class honours degree or equivalent, and/or a good MSc Degree in Computer Science, Electronic Engineering, Music/Audio Technology, or a related discipline. Knowledge of digital signal processing and/or machine learning is desirable, as well as programming experience in, e.g. MATLAB, Python, Java, C++ or similar. Experience in research and a track record of publications is advantageous. Formal music training is also desirable for the 3rd topic. There is scope to tailor the research to the interests and skills of the successful candidate.

SUPERVISION: The candidate will be supervised by Dr Emmanouil Benetos (http://www.eecs.qmul.ac.uk/~emmanouilb/). The project will be based in the School of EECS, and the student will join a group of around 60 full-time PhD students, post-doctoral researchers and academics in the Centre for Digital Music (http://c4dm.eecs.qmul.ac.uk/), a world-leading multidisciplinary research group in the field of Music & Audio Technology.

FUNDING: The studentship is for 3 years, and covers student fees as well as a tax-free stipend of 16,057 GBP per annum.

To apply, please follow the on-line process at (http://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 two questions: (i) Why are you interested in the topic described above? (ii) What relevant experience do you have? Your 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 . Informal enquiries about the studentship can be made by email to Dr Benetos (emmanouil.benetos@xxxxxxxxxx).

The closing date for the applications is 29 February 2016; interviews are expected to take place during March 2016.

-- 
Dr Emmanouil Benetos
RAEng Research Fellow, Lecturer
Centre for Digital Music
School of Electronic Engineering and Computer Science
Queen Mary University of London
Tel: +44 (0)20 7882 7986 
http://www.eecs.qmul.ac.uk/~emmanouilb/