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Position: Research Associate
Institution: University of Kent
Department: School of Computing
Location: Canterbury, Kent, United Kingdom
Duties: To develop signal processing algorithms to analyse electroencephalogram signals obtained from volunteer subjects during perception of different LED based brake lights in order to accurately measure the recognition ability and using this to improve the design of brake lights. The main objective of such a technology would be to use the characterised factors to promote faster driver perception, allowing manufacturers to develop new LED based brake light designs in future that are safer
Requirements: PhD (or nearing completion of study for one) or equivalent, in Computer Science, Engineering, Mathematics, or a closely related discipline, especially with research interests in practical applications of technologies (e.g. signal analysis, data mining/machine learning, information retrieval, and statistics), or other related topics. In-depth knowledge and hands-on experience with practical applications of EEG and/or fNIRS technologies with visual stimulus. Excellent signal processing and machine learning knowledge and excellent Matlab programming skills
   
Text: Research Associate Ref STM0955 Location Chatham Job Type Research Contract Type Fixed Term Salary Type Per Annum Salary (£) 34189 - 39609 STM0955, School of Computing, Closing date: 02 Oct 2018 Grade 7: £34,189 - £39,609 per annum, fixed term and full-time The School of Computing wishes to appoint a Research Associate to work alongside Dr Palaniappan Ramaswamy, Professor Ian McLoughlin and Professor Howard Bowman to develop signal processing algorithms to analyse electroencephalogram signals obtained from volunteer subjects during perception of different LED based brake lights in order to accurately measure the recognition ability and using this to improve the design of brake lights. The main objective of such a technology would be to use the characterised factors to promote faster driver perception, allowing manufacturers to develop new LED based brake light designs in future that are safer. This is a full time and fixed term post for a duration of 24 months and will provide the successful candidate with a rich collaborative environment: it is positioned within the vibrant and expanding Data Science Research Group at University of Kent’s School of Computing Medway campus. As a Research Associate you will: • Develop EEG and/or fNIRS response protocols and collect data from volunteer subjects and various user groups in both lab and real-world settings • Contribute to the development, integration, analysis and visualisation methods for analysing quantitative EEG and fNIRS data • Assist in the writing up of results for publication in leading academic journals as well as contributing to patent write up To succeed in this role you will have: • A PhD (or nearing completion of study for one) or equivalent, in Computer Science, Engineering, Mathematics, or a closely related discipline, especially with research interests in practical applications of technologies (e.g. signal analysis, data mining/ machine learning, information retrieval, and statistics), or other related topics. • In-depth knowledge and hands-on experience with practical applications of EEG and/or fNIRS technologies with visual stimulus. • Excellent signal processing and machine learning knowledge and excellent Matlab programming skills The School of Computing at Kent is a welcoming and supportive environment that has been recognised with a Bronze Athena SWAN award. We are a well-balanced, inclusive and diverse community that aims to further enhance our achievements and reputation in teaching, research and innovation. The School is located on two impressive campuses at Canterbury and Medway. Both are safe, friendly, well-equipped and in desirable locations, with excellent schools and a wealth of cultural links and superb transport connections. Start date for applications: 31 August 2018 Closing date for applications: 02 October 2018 Interviews are to be held: 09 October 2018 Please see the links below to view the full job description and also to apply for this post. If you require further information regarding the application process please contact The Resourcing Team on jobs@kent.ac.uk quoting ref number: STM0955 Please note - applications must be made via the University’s online application system. You will be required to fill in the main details section of the application form as well as upload your CV and a cover letter. Your cover letter should clearly and explicitly address the requirements of the Person specification and you should provide clear evidence and examples in your application which back-up any assertions you make in relation to each criterion. We recommend a maximum of 4 x A4 sides for this document. Full Job Description STM0955 - Additional Information.pdf STM0955- Job description.pdf
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