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Position: Research Fellow - Attention and Electroencephalography (EEG)
Institution: University College London
Department: Institute of Cognitive Neuroscience
Location: London, United Kingdom
Duties: The research aims to provide a new understanding of attention during real-life tasks, and within the autonomous car, using a combination of EEG, behavioural and eye tracking measures of attention, working memory and perception. The post holder will be responsible for the design and running of behavioural, neuroimaging and other cognitive neuroscience experiments with humans, both in the laboratory and within the car, as well as for recording, analysing and writing up the results
Requirements: Applicants should hold or expect to shortly hold a PhD with a record of success in research (as evidence in publications) in cognitive neuroscience (perferably including neuroimaging using the methods of EEG or MEG). Applicants are expected to have excellent quantitative and programming skills in Matlab, Python or equivalent as well as a strong written and verbal communication skills. Experience with advanced methods of signal processing, image processing, and computational modelling would be highly desirable
   
Text: Research Fellow - Attention and Electroencephalography (EEG), - Ref:1799416 Click here to go back to search results Apply Now UCL Department / Division Institute of Cognitive Neuroscience Location of position London Grade 7 Hours Full Time Salary (inclusive of London allowance) ?35,328 - ?42,701 per annum Duties and Responsibilities Applications are invited for a postdoctoral research fellow position (i.e. a postdoc) in UCL Attention and Cognitive Control Laboratory at the Institute of Cognitive Neuroscience, supervised by Prof Nilli Lavie. The project is funded by Jaguar Land Rover jointly with the EPSRC as a part of the program to develop fully autonomous cars: Towards Autonomy - Smart and Connected Control (TASCC) https://www.epsrc.ac.uk/newsevents/news/jlrannouncesautonomousvehicalresearchprogramme/ Our project is named CogShift and is now co-led by Prof Nilli Lavie at UCL and Dr James Brighton at Cranfield. The research aims to provide a new understanding of attention during real-life tasks, and within the autonomous car, using a combination of EEG, behavioural and eye tracking measures of attention, working memory and perception. The post holder will be responsible for the design and running of behavioural, neuroimaging and other cognitive neuroscience experiments with humans, both in the laboratory and within the car, as well as for recording, analysing and writing up the results. The position is funded for one year in the first instance, and is available to start as soon as possible. Key Requirements Applicants should hold or expect to shortly hold a PhD with a record of success in research (as evidence in publications) in cognitive neuroscience (perferably including neuroimaging using the methods of EEG or MEG). Applicants are expected to have excellent quantitative and programming skills in Matlab, Python or equivalent as well as a strong written and verbal communication skills. Experience with advanced methods of signal processing, image processing, and computational modelling would be highly desirable. Further Details Applicants are invited to apply by clicking on the 'Apply Now' button below. A job description and person specification can be accessed at the bottom of this page. For more information about the ICN Attention Lab visit the lab website: http://www.icn.ucl.ac.uk/lavielab If you have any queries regarding the vacancy or the application process, please contact Lucy Spikesley - l.spikesley@ucl.ac.uk UCL Taking Action for Equality Closing Date 26 Apr 2019 Latest time for the submission of applications 23:59 Interview date TBC This appointment is subject to UCL Terms and Conditions of Service for Research and Support Staff. Please use these links to find out more about UCL working life including the benefits we offer and UCL Terms and Conditions related to this job. Job Description and Person Specification Apply Now
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