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Marie Sklodowska-Curie ESR in Sound Scene Analysis
Department of Electrical & Electronic Engineering
£29,500 to £32,900
||Tuesday 24 March 2015
||Thursday 30 April 2015
Wednesday 06 May 2015
Marie Curie Annual Allowance (Pre-Employer/Employee Tax): €44,896
Marie Curie Annual Mobility Allowance & Family Allowance (Pre-Employer/Employee Tax): €7,200 & €6,000
MacSeNet is an EU-funded, Marie Sklodowska-Curie Innovative Training Network, bringing together leading academic and industry groups to train a new generation of interdisciplinary researchers in efficient Machine Sensing theory and algorithms.
There are 18 Marie Sklodowska-Curie Early Stage Researcher (ESR) positions (2 here at Surrey), which allow the researcher to work towards a PhD. The ESRs will be recruited to start mid 2015 for a duration of 36 months.
Each ESR will be working on an independent personal project and will have secondments linked to their research to other partners in the network, the planned secondments are listed below but may change as the individual projects evolve. They will also attend ITN progress meetings and Training events throughout Europe and possibly conferences and events internationally.
Marie Sklodowska-Curie ESRs are paid a competitive salary which is adjusted for their host country. Please see the individual positions below to find the annual salary for that host country (figures are given in Euros prior to employer and employee tax being deducted). Since the ESR positions include secondments to other hosts and for the researcher to move countries the EU also provides a Mobility Allowance, this is higher for researchers who have a family (family is defined as persons linked to the researcher by (i) marriage, or (ii) a relationship with equivalent status to a marriage recognised by the national legislation of the country of the beneficiary or of the nationality of the researcher, or (iii) dependent children who are actually being maintained by the researcher).
ESRs should be within four years of the diploma granting them access to doctorate studies at the time of recruitment.
In addition, to be eligible for a position as a Marie Sklodowska-Curie Early Stage Researcher you must not have spent more than 12 months in the host country in the 3 years prior to starting.
This exciting project will develop new algorithms suitable for sound scene analysis applications, such as sound-based security alarm systems or home acoustic event detection.
Human listeners appear to have an innate and effortless ability to isolate, identify, and attend to one sound source while suppressing others. In this project, we would like to be able to explore computer algorithms to explore this task, to find the direction and identity of sound signals in an audio scene, and also to extract one identified sound source from a mixture. There has been relatively little research on analysis and recognition of non-speech, non-music sound scenes. An increasing interest emerges recently in this area, such as the international Multimedia Event Detection (MED) track of the TRECVID competition (since 2010) which concerns classification of audiovisual archive clips such as “baking a cake” or “birthday party”, and a data challenge on Detection and classification of acoustic scenes and events (D-CASE) which attracted 18 submissions, using a wide variety of methods from spectro-temporal modulations classified with support vector machines (SVMs), to deep learning with sparse restricted Boltzmann machines (RBMs).
The candidate will investigate new methods for sound scene analysis, building structural models based on separate analysis of “foreground” sound events and “background” sound textures. We expect to use structured sparse models and tensor models, and develop new models based on dynamic timbre of sounds inspired by physical object models. The candidate will develop a methodology for the challenging problem of audio source identification and separation. By specifically identifying sources and their characteristics, we will also expect to obtain higher quality source separation than generic audio source separation methods. Deep learning based feature representation and sound identification techniques will also be studied.
CVSSP is one of the major research centres of Surrey’s Department of Electronic Engineering (EE), the top ranked UK EE department in both the RAE 2008 and in the national league tables. CVSSP is the largest research centres in the UK focusing on Computer Vision, graphics and signal processing, with 120+ members comprising academic and support staff, research fellows and PhD students.
Informal enquires are welcome and should be made to Dr Wenwu Wang or Prof Mark Plumbley.
Scientific: Fraunhofer IDMT, Germany, 3 months, for training in physical modelling of sound objects.
Cross-Sector: Audio Analytic, UK, 3 days/month, for training and applications in real-world audio event detection.
The successful applicant is expected to have an excellent mathematical and programming background, with an MSc or equivalent related to signal processing, machine learning, and audio engineering. Programming skills in Matlab or C/C++ are required as is a high level of English (IELTS average 6.5). Unfortunately we are not able to sponsor visa's for this position so the applicant should have the right to work in the UK.
Your application must include
your completed eligibility form.
a letter of motivation including a maximum 1-page statement explaining how your research interests, skills and experience are relevant to the position.
Transcripts of your undergraduate (and master) studies.
certificates of qualifications (such as BSc and MSc degree certificates, and any other certificates of excellence).
If you are not eligible for the positions here at CVSSP please do investigate those with our other partners http://macsenet.eu/
The salary for this position is subject to currency fluctuation, researchers will be paid the equivalent GBP amount of the Marie Sklodowska-Curie Allowance after Employer taxes have been paid. The ESR should expect to pay their employee taxes by PAYE.
The closing date for this job opportunity has now passed, and applications are no longer being accepted for this position
For more information and to apply online, please download the further details and click on the 'apply online' button above.
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