UK: 2 PhD studentships – University of Reading

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The School of Systems Engineering at the University of Reading is offering 2 fully-funded studentships.  The candidates must satisfy EPSRC requirements, being either a UK citizen or EU citizen with 3 years UK residency. The studentship comprises the fee at the UK/EU rate and a stipend (£13,290 in 2009/2010).

The 2  studentships will be awarded to two of the projects described below, according to the academic excellence of the candidate and their match to a particular project.

Interactive Technologies for Treating Alcohol Related Brain Injury

Alcohol related brain injury (ARBI) refers to physical impairment of the brain due to excessive alcohol consumption.  Characteristics commonly associated with ARBI include cognition and memory problems (e.g. confusion about time and place, impaired attention and concentration) and physical impairment (e.g. poor balance, pain in the extremities), with symptoms ranging from mild to severe.

This studentship will  design and evaluate interactive technologies to support the assessment, rehabilitation and ongoing care of people with alcohol related brain injury.  The candidate will work closely with end users, carers, and providers of community-based support services to ensure that the technology is effective and appropriate, and likely to be adopted widely.

For informal inquiries, please contact Dr. Faustina Hwang (

A Tool for Inferring Patterns of Web Usage and Information Sharing Using TweetMeme Data

This studentship will develop a tool for inferring patterns of Web usage and information sharing using data from, a Web site that tracks Web pages being shared across Twitter. TweetMeme is now tracking 500 million web pages a day, and has given the University of Reading exclusive access to its data. Analyzing this data will lead to rich insights into the behaviour of Web users by identifying patterns of content consumption and sharing. Applications of the results include the development of novel search engine ranking algorithms, predicting users’ interests based on their sharing behaviour, and the development of new models of viral content across the Web.

For informal inquiries, please contact Dr. Mike Evans (

Fusing LIDAR with Aerial Images in Identification of Tree Species

Computer vision technology has been found to be an important application in remotely sensed data understanding. This studentship exploits airborne LIDAR (LIght Detection And Ranging) and its co-registered aerial images to identify tree species. Different from existing approaches, the proposed research focuses on tree leaf shape recovery from very low resolution images in association with tree profile provided by LIDAR in tree species identification. Potential applications of the research cover forest-monitoring for eco-system analysis, forest growth modelling and fire risk assessment. The results of the research can also be used for city planning and forest management. Detecting drug plants from remotely sensed data may also fall in the application area.

For informal inquiries, please contact Dr. Hong Wei (

Tracking and Target Capture in a Cognitive Robot

This studentship will apply techniques from computational neuroscience to simple visual motor tasks with two broad objectives: first to understand processing in the sensory-motor areas of the brain, and second to make modern robots more robust and able to adapt to their environment. Tasks envisioned for an upper torso robot might range from lighting a candle to placing chess pieces on a board so comparison can be made with a 5 year old child doing a similar task.

For informal inquiries, please contact Prof. William Harwin (

Applicants would normally be expected to achieve or have achieved first class/upper second honours degree or Master degree in Computer Science, Cybernetics, Electronic Engineering, Information Technology or related area. Applicants with an interest in and experience of the project area will be given priority.

Applicants should send a completed application form (from and a covering letter explaining why they have selected the project they are applying for.

Applications should be emailed to by 27 August 2010, with the subject line: PhD Studentships 2010/13.

Interviews will be held on 7 September 2010.

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