RSS feeds can deliver the latest InfoLab21 news and events direct to your browser without you having to visit the website.
In most browsers you can click on an RSS link and choose to subscribe to the feed to add it to your favourites or bookmarks.
PhD Studentship - School of Computing and Communications
Autonomous Object Detection and Tracking in Real Time
Lancaster University, School of Computing and Communications
Minimum of £15,590 including a top up of £2K pa by the sponsoring company (Thales UK)
Applications are invited for a 3.5-year PhD studentship in Autonomous Object Detection and Tracking in Real Time commencing 1 January 2013 (or as soon as the post is filled in but no later than 1 October 2013.
About the project
The studentship is funded by the Engineering and Physical Sciences Research Council (EPSRC) and Thales UK. The project's aim is to investigate and develop innovative methods, algorithms and software for real-time on-board processing of climate science data in terms of identifying dynamically evolving clusters and autonomously monitor, model and extract knowledge from the data streams.
The aim is for this studentship to address both basic theoretical and application research questions relevant to the real-time processing and following broadcasting the sensor data from the unmanned aerial vehicles (UAV). Basic questions include those of development of novel real-time computationally efficient methods aiming to autonomously comprehend the prodigious amounts of data that can be generated and thus to overcome the bandwidth constraint in the exploitation of next generation sensor performance. Application research will centre on developing new algorithms, software implementation serving the experimental elements of the project for real-time data stream processing for object detection and tracking by UAV. The studentship thus offers the opportunity to participate in the development of new theoretical and application advances of research methodology and development of related algorithms and software as well as to be closely related and provide this to the industrial sponsor.
Supervisors and Location
The studentship will be supervised by Dr Plamen Angelov, who will provide the expertise in autonomous systems, machine learning and pattern recognition and provide the day-to-day pastoral supervision. An industrial sponsor is also assigned from the sponsoring company. Dr. Glen Davidson is based in Crawley but the meetings with the student will also be in Cheadle Heath, Greater Manchester. The studentship will be based in Lancaster University's Infolab21 - a Centre of Excellence in ICT the School of Computing and Communications and its Intelligent Systems research Area, in particular. This provides an excellent opportunity for professional and personal development.
Due to EPSRC and company requirements, this award is only available to UK citizens. This studentship is fully funded by EPSRC and Thales UK and covers all fees, an annual maintenance award of a minimum of £15,590 per annum (2012/13 level) over 3.5 years.
Applicants should hold (or expect to obtain) a minimum upper-second class honours degree or equivalent in a discipline related to machine learning, pattern recognition, computational intelligence or broader computer science and/or electrical engineering, mathematics and statistics or physics. Technical aptitude and a willingness to learn fast new areas of research will also be essential. Because this studentship is a part of a project and includes communication with the industrial sponsors, excellent communications skills are required.
How to apply
To apply, please send the following documents by email to Dr Plamen Angelov (email@example.com) a CV (including names and contact details of two referees) as well as a Covering letter (including the motivation and a research proposal/statement).
Closing date: 15 December 2012
Wed 17 October 2012