Postdoctoral Research Fellow on "Statistical Anomaly Detection", CVSSP, University of Surrey, U.K. (Closing: Feb 28th, 2013) ("Wenwu W. Wang" )

Subject: Postdoctoral Research Fellow on "Statistical Anomaly Detection", CVSSP, University of Surrey, U.K. (Closing: Feb 28th, 2013) From: "Wenwu W. Wang" <W.Wang@xxxxxxxx> Date: Wed, 13 Feb 2013 12:28:59 +0000 List-Archive:<http://lists.mcgill.ca/scripts/wa.exe?LIST=AUDITORY> --_000_EBCDBA8C34662B48ADCB9C62B3E9B9A9ACA3DD5F64EXMB05CMSsurr_ Content-Type: text/plain; charset="iso-8859-1" Content-Transfer-Encoding: quoted-printable Research Fellow Statistical anomaly detection Centre for Vision Speech and Signal Processing (CVSSP) University of Surrey, United Kingdom Salary: =A329,541-=A331,331 per annum (Subject to qualifications and experience) Applications are invited for a three-year postdoctoral research fellow posi= tion available at CVSSP, starting on Monday, April 1, 2013, to work on a pr= oject entitled "Signal Processing Solutions for a Networked Battlespace", f= unded 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 acad= emic experts from Loughborough, Surrey, Strathclyde and Cardiff (LSSC) Univ= ersities together with six industrial project partners QinetiQ, Selex-Galil= eo, Thales, Texas Instruments, PrismTech and Steepest Ascent. The overall a= im 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 plat= forms, in order to retain military advantage and mitigate smart adversaries= who present multiple threats within an anarchic and extended operating are= a (battlespace). The research fellow will be expected to work in close coll= aboration with our academic and industrial partners together with members o= f the lead consortium based at Edinburgh and Heriott Watt Universities. The prospective research fellow will be expected to develop algorithms and = systems for automated statistical anomaly detection and classification in h= igh dimensions for the networked battlespace. In particular, he/she will de= velop algorithms for automatic detection of anomalies from multidimensional= , undersampled, non-complete datasets and unreliable sources, and solutions= to anomaly detection with the presence of uncertainties and in complex net= works (graphs), e.g., using domain knowledge. Successful applicants will join the CVSSP, a leading research group in sens= ory (visual and auditory) data analysis and interpretation, and will work c= losely 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 wit= h more than 120 researchers, with core expertise in Signal Processing, Imag= e and Video Processing, Pattern Recognition, Computer Vision, Machine Learn= ing and Artificial Intelligence, Computer Graphics and Human Computer Inter= action. 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 res= earch classified as either 4* ("world-leading") or 3* ("internationally exc= ellent"). Applicants should have a PhD degree or equivalent in electrical and electro= nic engineering, computer science, mathematical science, statistics, physic= s, or related disciplines. Applicants should be able to demonstrate excelle= nt mathematical, analytical and computer programming skills. Advantages wil= l be given to the applicants who have experience in anomaly detection, stat= istics, machine learning, signal processing, and/or pattern recognition. For informal inquiries about the position, please contact Dr Wenwu Wang (w.= wang@xxxxxxxx) or Prof Josef Kittler (j.kittler@xxxxxxxx). 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 co= ntact Mr Peter Li, HR Assistant on Tel: +44 (0) 1483 683419 or email: k.li@xxxxxxxx= surrey.ac.uk The closing date for applications is Thursday February 28th, 2013. For further information about the University of Surrey, please visit www.su= rrey.ac.uk. We acknowledge, understand and embrace cultural diversity. --_000_EBCDBA8C34662B48ADCB9C62B3E9B9A9ACA3DD5F64EXMB05CMSsurr_ Content-Type: text/html; charset="iso-8859-1" Content-Transfer-Encoding: quoted-printable <html dir=3D"ltr"><head> <meta http-equiv=3D"Content-Type" content=3D"text/html; charset=3Diso-8859-= 1"> <meta name=3D"GENERATOR" content=3D"MSHTML 9.00.8112.16441"> <style id=3D"owaTempEditStyle"></style><style title=3D"owaParaStyle"></style> </head> <body ocsi=3D"x"> <div style=3D"FONT-FAMILY: Tahoma; DIRECTION: ltr; COLOR: #003300; FONT-SIZ= E: x-small"> Research Fellow <= font color=3D"#000000">Statistical anomaly detection= Centre for Vision Speech and Signal Processi= ng (CVSSP) University of Surrey, United Kingdom<= /p> Salary: =A329,541-=A331,331 per annum (Subject to qualifications and experience)</= font> Applications are invited for a three-year postdoctoral research fellow position</f= ont> available at CVSSP, starting on Monday, April 1, 2013, to work on a pr= oject entitled "Signal Processing Solutions for a Networked Battlespac= e", funded by the Engineering and Physical Sciences Research Council (EPSRC) and Defence Science and Technology Labor= atory (Dstl), as part of the Ministry of Defence (MoD) University Defence R= esearch Centre (UDRC) Scheme in signal processing. This project will be und= ertaken 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 over= all aim of the project is to provide fundamental signal processing solutions to enable intelligent and robust p= rocessing of the very large amount of multi-sensor data acquired from vario= us networked communications and weapons platforms, in order to retain milit= ary advantage and mitigate smart adversaries who present multiple threats within an anarchic and extended o= perating area (battlespace). The research fellow will be expected to work i= n close collaboration with our academic and industrial partners together wi= th members of the lead consortium based at Edinburgh and Heriott Watt Universities. The prospective research fellow will be expe= cted to develop algorithms and systems for automated statistical anomaly de= tection and classification in high dimensions for the networked battlespace. In particular, he/she will develop algorith= ms for automatic detection of anomalies from multidimensional, undersampled= , non-complete datasets and unreliable sources, and solutions to anomaly de= tection with the presence of uncertainties and in complex networks (graphs), e.g., using domain knowledge. 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 t= he 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 Gr= aphics and Human Computer Interaction. CVSSP forms part of the Department o= f 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 resea= rch classified as either 4* ("world-leading") or 3* ("intern= ationally excellent"). Applicants should have a PhD degree or equiv= alent in electrical and electronic engineering, computer science, mathemati= cal science, statistics, physics, or related disciplines. Applicants should be able to demonstrate excellent mathematic= al, analytical and computer programming skills. Advantages will be given to= the applicants who have experience in anomaly detection, statistics, machi= ne learning, signal processing, and/or pattern recognition. For informal inquiries about the position, p= lease contact Dr Wenwu Wang (w.wang@xxxxxxxx) or Prof Josef Kittler (j.= kittler@xxxxxxxx). For an application pack and to apply on-line= please go to our website: http://www.surrey.ac.uk/vacancies. If you are un= able to apply on-line please contact Mr Peter Li, HR Assistant on Tel: +44 (0) 1483 683419 or email: k.li@xxxxxxxx= uk The closing date for applications is Thursday February 28th, 2013. For further information about the University= of Surrey, please visit www.surrey.ac.uk. We acknowledge, understand and embrace cultu= ral diversity. </div> </body> </html> --_000_EBCDBA8C34662B48ADCB9C62B3E9B9A9ACA3DD5F64EXMB05CMSsurr_--

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