TWO fully funded PhDs paying £17,000 p.a. + UK/EU fees + travel budget - deadline AUGUST 10th

Organization: 
UCL SECReT, University College London, UK
Email: 
news@ucl-dscs-mail.org.uk
Job Description: 

£17,000 tax-free stipend+ full UK/EU fees + research and conference travel budget for TWO 4-year PhD positions. For full details and how to apply click on the links below:

http://www.ucl.ac.uk/secret/homepage/

Wideband frequency reconfigurable antennas
http://www.ucl.ac.uk/secret/secret_news/lg3-funding

AND

Statistical signal processing and machine learning for network traffic anomaly detection
http://www.ucl.ac.uk/secret/secret_news/statistical-signal

Application deadline: 10th AUGUST 2012, 4pm

Applicants must be UK/EU nationals.

The candidate must start October 2012.

The above PhDs will be undertaken within the UCL Security Science Doctoral Training Centre (UCL SECReT), working with other relevant UCL departments. See below for details.

Learn about UCL SECReT

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Wideband frequency reconfigurable antennas

This proposal would focus on optimizing the reconfigurable antenna design parameters for wireless communications at different frequency bands. The novel reconfigurable antenna are able to operate at multiple of tens of MHz bands offering uni-directional radiation pattern, good gain and the ability to maintain higher signal to noise ratio over the whole of the operating range of conventional broadband antenna. Rapid low loss electronic switching mechanism allow for real-time control of the antenna re-configuration.

The ideal candidate is expected to have strong electromagnetic and RF circuit design background.

The research will be undertaken within the UCL Security Science Doctoral Training Centre (UCL SECReT) and the UCL Dept. of Electronic and Electrical Engineering. The research is partly funded by the L-3 TRL Technology. Because the project is in collaboration with a UK defence company, there is a strong preference for a candidate who is eligible for UK security clearance.

Statistical signal processing and machine learning for network traffic anomaly detection

This project will develop advanced multivariate statistical and machine learning methodology for the analysis of network traffic measurement data. The aim is to deliver robust detection of hostile cyber activity. Several open problems will be addressed, including the choice of background model, features, and classifiers; and possible incorporation of multiresolution inferential methodology, which may include extensions to wavelet-Bayesian Markov chain Monte Carlo change point approaches.

The ideal candidate will have a strong interest in exciting recent developments in the convergent disciplines of computational statistics, machine learning, and signal processing.

The research will be undertaken within the UCL Security Science Doctoral Training Centre (UCL SECReT) and the UCL Dept of Statistical Science. The research is funded by the UK Ministry of Defence and will involve some collaboration with the Defence Science and Technology Laboratory.

Job Categories: 
Universities and colleges
Deadline for Application: 
Aug 10 2012
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