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Research Fellow vacancy on Blind Source Separation at CVSSP/Surrey/UK (Closing date: March 17th, 2013, i.e. this weekend)

Dear list,
Please feel free to circulate the above job advert to those who you think might be interested. Thank you.
Kind regards,


Research Fellow
Low-Complexity Source Separation Algorithms
Centre for Vision Speech and Signal Processing (CVSSP)
Salary: £29,541-£30,424 per annum
(Subject to qualifications and experience)
Applications are invited for a three-year postdoctoral research fellow position available at CVSSP, starting on Monday, April 1, 2013, to work on a project entitled "Signal Processing Solutions for a Networked Battlespace", funded by the Engineering and Physical Sciences Research Council (EPSRC) and Defence Science and Technology Laboratory (Dstl), as part of the Ministry of Defence (MoD) University Defence Research Centre (UDRC) Scheme in signal processing. This project will be undertaken by a unique consortium of academic experts from Loughborough, Surrey, Strathclyde and Cardiff (LSSC) Universities together with six industrial project partners QinetiQ, Selex-Galileo, Thales, Texas Instruments, PrismTech and Steepest Ascent. The overall aim of the project is to provide fundamental signal processing solutions to enable intelligent and robust processing of the very large amount of multi-sensor data acquired from various networked communications and weapons platforms, in order to retain military advantage and mitigate smart adversaries who present multiple threats within an anarchic and extended operating area (battlespace). The research fellow will be expected to work in close collaboration with our academic and industrial partners together with members of the lead consortium based at Edinburgh and Heriott Watt Universities.
The prospective research fellow will be expected to develop low-complexity robust algorithms for underdetermined, convolutive signal separation, broadband distributed beamforming. The work will be facilitated by low-rank and sparse representations, and directed toward fast implementations. He/she will develop robust source separation algorithms in highly dense signal environments, with the presence of uncertainties, such as weak signals and the unknown number of targets.
Successful applicants will join the CVSSP, a leading research group in sensory (visual and auditory) data analysis and interpretation, and will work closely with Dr Wenwu Wang, Prof Josef Kittler and Dr Philip Jackson. CVSSP is one of the largest UK research groups in machine vision and audition with more than 120 researchers, with core expertise in Signal Processing, Image and Video Processing, Pattern Recognition, Computer Vision, Machine Learning and Artificial Intelligence, Computer Graphics and Human Computer Interaction. CVSSP forms part of the Department of Electronic Engineering, which received one of the highest ratings (joint second position across the UK) in the last research quality assessment, i.e. 2008 RAE, with 70% of its research classified as either 4* ("world-leading") or 3* ("internationally excellent").
Applicants should have a PhD degree or equivalent in electrical and electronic engineering, computer science, mathematical science, statistics, physics, or related disciplines. Applicants should be able to demonstrate excellent mathematical, analytical and computer programming skills. Advantages will be given to the applicants who have experience in sparse representations, blind source separation, low-rank linear algebra, and/or machine learning.
For informal inquiries about the position, please contact Dr Wenwu Wang (w.wang@xxxxxxxxxxxx).
For an application pack and to apply on-line please go to our website: http://www.surrey.ac.uk/vacancies. If you are unable to apply on-line please contact Mr Peter Li, HR Assistant on Tel: +44 (0) 1483 683419 or email: k.li@xxxxxxxxxxxx.
The closing date for applications is March 17th, 2013.
For further information about the University of Surrey, please visit www.surrey.ac.uk.
We acknowledge, understand and embrace cultural diversity.

Dr Wenwu Wang
Centre for Vision Speech and Signal Processing
Department of Electronic Engineering
University of Surrey
Guildford GU2 7XH
United Kingdom
Phone: +44 (0) 1483 686039
Fax: +44 (0) 1483 686031
Email: w.wang@xxxxxxxxxxxx

From: AUDITORY - Research in Auditory Perception [AUDITORY@xxxxxxxxxxxxxxx] On Behalf Of Mark Cartwright [mcartwright@xxxxxxxxx]
Sent: 12 March 2013 11:12
To: AUDITORY@xxxxxxxxxxxxxxx
Subject: [AUDITORY] SocialEQ - Audio Descriptor Data Collection


Apologies for potential cross-postings

Dear community,

We are conducting a study on adjectives for sounds. We are specifically interested in adjectives that describe characteristics which can be modified by audio production tools, such as reverberation and equalization. We are hoping that you can help us with a data collection of such adjectives by using our new web-based tool, SocialEQ - http://socialeq.org.

SocialEQ is a tool to learn the meaning of sound adjectives that relate to equalization. We'd like you to teach the SocialEQ equalizer an adjective that you would use to describe a sound. Once the system thinks it understands, it will give you a slider to make the sound more or less like the adjective (for example, more or less "bright"). After that task is complete, we will present you with a survey. The whole thing should take about five minutes.

To participate, go to http://socialeq.org.

Thank you for your time!

Best regards,

Mark Cartwright <mcartwright@xxxxxxxxxxxxxxxxxx>
Bryan Pardo <pardo@xxxxxxxxxxxxxxxx>

The Interactive Audio Lab
Electrical Engineering and Computer Science
Northwestern University