2007-07-10: Job Offer: KTP associate in Information Visualisation (Oxford, UK)

From InfoVis:Wiki
Revision as of 15:59, 10 July 2007 by Frmitchell (talk | contribs)
(diff) ← Older revision | Latest revision (diff) | Newer revision → (diff)
Jump to navigation Jump to search

Oxford Brookes University, School of Technology & Nominet KTP Research Fellow[edit]

Starting salary: £30-34,000, depending on experience

Nominet is an award winning organisation that operates at the heart of e-commerce in the UK, running the world’s forth largest Internet registry. Nominet is entrusted with the management of UK internet domain names.

A DTI funded Knowledge Transfer Partnership (KTP) has been awarded to Nominet and Oxford Brookes University for two years. Successful candidates will develop technology to detect fraudulent use of the domain name registry using visualisation techniques. The post is based at Nominet (shortly relocating to new state-of-the-art premises on the Oxford Science Park) and the post holder will work closely with Nominet’s highly experienced development team.

Key tasks:

  • identify, through theory and experiment, promising visualization techniques
  • develop software tools that will form the basis of operational deployment within Nominet
  • prepare and deliver conference and journal papers and disseminate the results within Nominet

You should have:

  • an honours degree (2:1 or above) in a numerate discipline such as computer science, physics, bio-informatics or mathematics awarded within the last five years (a higher degree in a relevant area would be an advantage)
  • a strong academic background involving the handling of very large, multi-variate, sparse data sets such as log files
  • the ability to demonstrate the applicability of state of the art visualization techniques to the detection of unusual patterns in this kind of data
  • proven ability with these visualization techniques
  • knowledge of the mathematical background underpinning visual data mining and ability to apply this to new problems
  • ability to create novel algorithms and convert these into production quality systems
  • excellent problem solving and programming skills
  • adaptability with a “can do” attitude and good team player skills

Further information and application forms can be found at