Application closing date: 22/04/2016
Start date: 01/09/2016
Research group: Music Technology Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra
Duration: 3 years Years Funding available
Applications are invited for two fully funded PhD studentships at the Music Group, Universitat Pompeu Fabra, Barcelona, Spain undertaking research into Technology Enhanced Learning of Music Instruments.
TELMI is a joint project of 3 academic and 2 industry partners: Universitat Pompeu Fabra, Spain; Royal College of Music, UK; University of Genova, Italy; HIGHSKILLZ, UK; SAICO INTELLIGENCE, S.L. Spain. The aim of the project is to study how we learn musical instruments, taking the violin as a case study, from a pedagogical and scientific perspective and to create new interactive, assistive, self-learning, augmented-feedback, and social-aware systems complementary to traditional teaching. As a result of a tightly coupled interaction between technical and pedagogical partners, the project will attempt to answer questions such as “How will the musical instrument learning environments be in 5-10 years time?” and “What impact will these new musical environments have in instrument learning as a whole?”. More information a bout the project can be found at http://mtg.upf.edu/node/3367
The student will be a member of the Music Technology Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra and will be supervised by Dr. Rafael Ramirez and Dr. Alfonso Perez-Carrillo. The successful candidate will pursue research at the intersection of audio and video signal processing, machine learning and cognitive sciences in the context of music performance pedagogy. The work will involve the development of multimodal signal processing algorithms, design of augmented visual feedback systems and the development of non-intrusive low-cost sensing systems for violin learning/teaching.
Candidates must have a good Master Degree in Computer Science, Electronic Engineering, Physics or Mathematics. Candidates must be confident in signal processing, have excellent programming skills, be fluent in English and possess good communication skills. Experience in machine learning and music performance would be an advantage, as would previous experience in research and a track record of publications. Interested candidates should apply by sending a full CV and a letter of interest to Dr. Alfonso Perez and Dr. Rafael Ramirez. Informal enquiries can be made by email to Dr. Alfonso Perez-Carrillo (alfonso [dot] perez [at] upf [dot] edu, http://www.dtic.upf.edu/~aperez/) and Dr. Rafael Ramirez (rafael [dot] ramirez [at] upf [dot] edu, http://www.dtic.upf.edu/~rramirez/).