To apply, please complete the Internships Application Form.
Applications must be made by 23rd March 2012.
This internship is available for the successful candidate to start as
soon as possible. Please indicate your availability on the application
form, where requested.
The modern web provides a rich
platform for people to interact, handle, consume and play with a variety of
digital content such as images, videos and audio material. A crucial point or
bottleneck of this interaction is the filtering of salient, relevant material
which a specific user would like to access at a given time. Traditional text
based search has been augmented to parse meta tags of content to facilitate
this filtering process and increasingly, crowd-sourced content-rating metrics
such as “Like”s aim to provide a useful measure of the quality or at least
desirability of content. While these measures attempt to go beyond traditional
search methods by incorporating human (crowd-sourced) feedback on content, the
information gathered and accessible through existing services is mostly of a
very basic and abstract nature (e.g. to like or not to like). A large number of
applications (both commercial and research) can potentially benefit from
readily available infrastructure which allows for a more fine-grained rating of
digital content based on an arbitrary set of designer-chosen metrics. Examples
of such rating services include the rating of digital images based on metrics
such as Humour, Anger, Quality, etc. and the comparison of images based on
those metrics (e.g. x is funnier than y). All of these services can easily be
transformed for other digital content such as audio or video.
As part of this internship, the
candidate will be expected to design a software component/web application which
provides a basic, crowd-sourced rating/comparison system for digital content.
The software component is expected to be a self-contained, configurable
component which is deployable online as a web-component using one or more of
the established website/blogging services such as WordPress, Blogger, etc.
As such, the development will
include the production of the actual web-component as well as a “configuration
suite” which allows the flexible configuration of the application for various
purposes (e.g. image rating or image comparison of 3 images). Finally, the
development will include the production of a set of integrated tools which
allow the processing of the collected rating-data according to both existing
and new A.I. techniques.
The ideal candidate will have significant experience in developing
web applications. In particular, experience with integrating web applications
and databases would be an advantage (preferably using cloud based services such as Microsoft Azure,
Amazon AWS). Experience with current webpage development tools such as
WordPress and Blogger is a bonus.
This internship is for 12 weeks (full-time) and is aimed at current postgraduate students, particularly PhD students. For PhD students who receive a stipend from their home university during the internship, a bursary of £300 per week will be available. For PhD students who suspend their stipend, a casual wage of £350 per week will be available, and this may be subject to deductions depending on the successful candidate's circumstances. In general, postgraduate students from The University of Nottingham are not eligible to apply, due to the nature of the funding source. Postgraduate students within the Horizon Doctoral Training Centre may apply to undertake this internship without receiving a bursary or casual wage.
The internship will be based at The University of Nottingham, on the Jubilee Campus (NG7 2TU) - this internship may not be undertaken remotely.
Informal enquiries may be made to email@example.com, however applications should be made using the following weblink. Applications to this email address will not be accepted.
Horizon Digital Economy Research, University of Nottingham Innovation Park, Triumph Road, Nottingham, NG7 2TU
firstname.lastname@example.org Office: +44 0115 8232554 Fax: +44 0115 8232551
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