[visionlist] Postdoctoral RA - Statistical Face Modelling and Super-resolution

[William Smith]

DSTL Project - Face Processing in High Volume, Low Quality Data Environments

Applications are invited for a Postdoctoral Research Assistant post within the Computer Vision and Pattern Recognition Research Group in the Department of Computer Science, University of York. The group is concerned with the development of novel computer vision and pattern recognition algorithms and models (seehttp://www.cs.york.ac.uk/cvpr).

The post is associated with a DSTL project considering model-driven 3D super-resolution of faces from high volume, low quality data. The work programme will focus on the creation of a part statistical/part data-driven model constructed using existing datasets and the development of algorithms for fitting the model to low quality data. The post provides an opportunity to work closely with partners in DSTL on real world vision problems.

Candidates must hold or expect to shortly obtain a PhD, or equivalent in computer vision, computer graphics or machine learning.  Candidates will be expected to have publications in these areas in international conferences or journals. Of particular relevance is statistical machine learning, super-resolution, optimisation and 3D computer vision.  Good programming and mathematical skills are essential and previous experience of statistical face modeling is beneficial.

The salary will be £30,122 per annum. This full time post will be offered on a fixed term contract for a period of 12 months and candidates must be available to start on the 1st of October 2012.

Informal enquiries may be made to Dr William Smith (email: william.smith at york.ac.uk).

Closing date for applications: 30 August 2012

For further details and application form, see here: http://tinyurl.com/c7embey


Dr William A. P. Smith
Lecturer in Computer Vision
Department of Computer Science
University of York, UK

Email: william.smith at york.ac.uk
URL: http://www.cs.york.ac.uk/~wsmith
Tel: +44 (0)1904 325575