Research Associate in Computational Statistics for Image Data - Ref:1430209
Salary: £33,353 - £40,313 per annum
Duration of post: 12 months in the first instance Closing date: 23rd September 2014 Project:
Start date: October/November 2014 or soon thereafter.
Applications are invited for a post-doctoral research associate position in the Department of Statistical Science at University College London, UK.
This DSTL-funded project will exploit exciting recent developments in applied and computational statistics and beyond to advance current understanding of how relational and contextual aspects of image data can contribute to tasks such as detection, classification, and segmentation.
The project will address the current need to progress new spatial-statistical models and computer-aided approaches that have the capability to capture both the rich statistical, and structural, interdependencies present in high-dimensional image data sets. The work will draw on the interacting and convergent fields of computational statistics, machine learning, statistical signal processing, and computer vision where recent activity has given rise to a wealth of concepts that attempt to describe both correlatory and relational interactions of heterogeneous data over, and between, multiple scales.
Image data sets taken from a selection of neoteric applications, including the life sciences, astronomy, and oceanography, will be considered.
Of some interest to this project is the use and development of graphs/graphlets, random fields and point processes, stochastic geometry, hierarchical representations, and/or multiresolution analyses to model the dependencies between key constituent parts of image data.
It is hoped that a somewhat more comprehensive, relational, description of the data will facilitate better, and more robust, detection and segmentation. The post-holder will have an interest in one or more of these (or allied) areas along with experience of some of the associated inferential/estimation machinery (such as Markov chain Monte Carlo, EM, LARS/lasso, ADMM, etc, and variants thereof). Good programming skills in Matlab, R, Python, and/or C/C++ are essential.
It is anticipated that the project will afford the opportunity for the post-holder to enjoy some collaboration with Dstl, industry, other universities in the UK (especially Cambridge, Bristol, and Imperial) and elsewhere, and multiple departments and centres at UCL, including the Centre for Computational Statistics and Machine Learning.
In particular, thanks to a series of recent grants, totalling over £1.3M, there will be ample opportunities for interaction with the immediate research group which currently comprises:
. one other research associate and three Phd students funded by Dstl
. one EPSRC-funded research associate
. two other Phd students funded by an ASTAR/UCL joint-scheme
The post comes with a generous travel and research expenses budget and is funded for 12 months in the first instance.
* How to Apply
To apply for the vacancy please click on the "Apply Now" button at:
Informal enquiries regarding the vacancy are welcomed and may be addressed to Dr James Nelson. See below links for contact details.