[apologies for the cross-posting, please circulate to colleagues as appropriate]
Dear All, Applications are invited for a fully funded PhD studentship at the Centre for Digital Music (C4DM)<http://c4dm.eecs.qmul.ac.uk/> undertaking research into Semantic Audio within the context of a European Union Horizon 2020-funded project Audio Commons<http://www.audiocommons.org/>. The project brings the success of Creative Commons to the world of audio. It aims to address several issues faced by the creative industries when using musical as well as non-musical audio material on the Web and aims to develop novel methods enabling the creation, access, retrieval and reuse of audio material in innovative new ways. Audio Commons is a joint project combining the strength of 3 academic and 3 industry partners; UPF, Spain, Queen Mary University of London, UK, University of Surrey, UK, AudioGaming, France, Waves, Israel and Jamendo Music, Luxembourg. The student will be a member of the Centre for Digital Music at Queen Mary University, School of Electronic Engineering and Computer Science. The student will be supervised by Dr. George Fazekas. The successful candidate will develop algorithms that combine audio signal processing for content analysis with semantic web technologies for gathering and analysing contextual information related to audio recordings. The work will involve the development technologies supporting the Audio Commons Ecosystem, developing novel signal processing and machine learning algorithms for content annotation, and conducting user studies to evaluate application specific prototypes, for instance novel tools for audio retrieval, sound design or music production, developed in collaboration with the project's industry partners. All nationals are eligible to apply for this studentship, which will start in February 2016. The studentship is for 3 years and covers student fees as well as a tax-free stipend of £19,200 per annum. Candidates must have a first-class honours degree or equivalent, or a good MSc Degree in Computer Science, Electronic Engineering, Physics or Mathematics. Candidates must be confident in signal processing and web technologies and have programming experience. Experience in Semantic Web (RDF, OWL, SPARQL) and machine learning would be an advantage, as would previous experience in research and a track record of publications. Informal enquiries can be made by email to Dr George Fazekas ([email protected]<mailto:[email protected]>) To apply, please follow the on-line process (www.qmul.ac.uk/postgraduate/apply<http://www.qmul.ac.uk/postgraduate/apply>) by selecting ‘Electronic Engineering’ in the ‘A-Z list of research opportunities’ and following 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? (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. This might be a chapter of your final year dissertation, or a published conference or journal paper. More details can be found at: www.eecs.qmul.ac.uk/phd/apply.php<http://www.eecs.qmul.ac.uk/phd/apply.php> The closing date for the applications is 5th. January 2016. Interviews are expected to take place during the week of 11th January 2016. Please note there are also post-doctoral positions available starting February or May 2016 (see my previous announcements). Best wishes, George Fazekas Lecturer in Digital Media, Centre for Digital Music (room CS414) School of Electronic Engineering and Computer Science Queen Mary, University of London Web: http://eecs.qmul.ac.uk/~gyorgyf/ Email: g.fazekas at qmul.ac.uk<http://qmul.ac.uk>
