Applications are invited 1 fully-funded PhD studentship, allied to the 5 year EPSRC and Digital Economy funded Programme Grant: Fusing Audio and Semantic Technologies for Intelligent Music Production and Consumption (FAST-IMPACt or FAST - see www.semanticaudio.ac.uk).
FAST-IMPACt aims to answer questions such as: How can next generation web technologies (Ontologies, Linked Data, Metadata) combined with music content analysis in the studio bring new value and functionality to producers, creators, consumers and intermediaries of music content? And how will both ends of the music value chain benefit from more engaging interactions (enhanced productivity, increased enjoyment and immersion) while creating or consuming music? And can intermediaries add value with semantically enhanced services? Helping us pursue this vision are national and international partners from academia and industry, including BBC R&D, Abbey Road, Solid State Logic, International Audio Labs and more. Candidates must have a first-class honours degree or equivalent, or a good MSc Degree in Computer Science, Electronic Engineering, Sound & Music Computing or equivalent. Candidates should be confident in digital signal processing and/or machine learning, and have programming experience in, e.g. MATLAB, Mathematica, Python, Java, C++ or similar. Experience in research and a track record of publications is very advantageous. Formal music training or sound engineering experience is also advantageous. Positions are available immediately. Only 1 place is available with full fees and stipend; but additional positions may be available for self-funded or part-funded applicants. Please apply online via the Queen Mary University of London application system, quoting the specific project(s) of interest. Enquiries may be addressed to mark.sand...@qmul.ac.uk. Projects titles are below. Fuller details of each of the projects below are available at http://tinyurl.com/jye2x69 [SAMI1] Studio Science: improving feature extraction in the studio; delivering new experiences to the consumer [SAMI2] Enhancing the music listening experience [SAMI3] Song level audio features for navigating large music collections [SAMI4] Note level audio features for understanding and visualising musical performance [SAMI5] Audio features for MIR based on human hearing physiology and neuroscience and on acoustics [SAMI6] Compression of individual instrument stems for compact multi-track audio formats -- professor mark sandler, CEng, FIEEE, FAES, FIET, FBCS royal society wolfson research merit award holder director of the EPSRC/AHRC CDT in media and arts technology (MAT) director of the centre for digital music (c4dm) school of electronic engineering and computer science queen mary university of london mark.sand...@qmul.ac.uk +44 (0)20 7882 7680 +44 (0)7775 016715 twitter: @markbsandler, follow the FAST-IMPACt Programme Grant @semanticaudio _______________________________________________ dupswapdrop: music-dsp mailing list music-dsp@music.columbia.edu https://lists.columbia.edu/mailman/listinfo/music-dsp
