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News and Resources for Members of the IEEE Signal Processing Society
(Source: Information from IEEE Jobsite)
Job Description: We are seeking one highly motivated postdoctoral fellow in computational neuroscience and signal processing to be part of an interdisciplinary research alliance working to develop computational models and data analysis methods in support of a research program in neuroergonomics (‘the study of the brain and body at work’).An overall goal of the research is to discover underlying principles describing the relationship of non-invasively recorded EEG brain dynamics and motivated behavior (recorded by body motion capture, eye tracking, etc) in interactive, information-rich human-system operating environments and to apply these principles to support overall performance of complex system operations.
The ideal candidate will have strong background in statistical learning, data analysis, and visualization with preferably research experience in neuroscience or cognitive science. The candidate will be based at University of Texas at San Antonio (UTSA) and needs to work closely with researchers and students at participating universities and to present their research at conferences and in the open research literature. The candidate will also collaborate with Army Research Laboratory (ARL), Aberdeen, MD, to assist data analysis from successively more complex and realistic experiments and with academic research groups at UC San Diego (Scott Makeig, Tzyy-Ping Jung, Roger Levy, Ken Kreutz-Delgatho, Angela Yu, Falko Kuester), University of Michigan (Dan Ferris), and other international groups at National Chiao Tung University, Taiwan (Chin-Teng Lin), and University of Osnabrück, Germany (Peter König).
Funding Period: Salary: $34k/year plus benefits. The project is in the second of five years of funding, with subsequent renewal for an equal period possible. The initial appoint period will be one year. Continuation of support will be contingent upon the performance of the candidate and availability of funds.
Instructions to Applicants: Applicants should submit a cover letter and CV, including the names and contact information of three references. Include in the cover letter accompanying the application a summary of your research experience and goals. Please send application materials by e-mail to:
Yufei Huang, Associate Professor, Department of Electrical and Computer Engineering, University of Texas at San Antonio; yhuang@utsa.edu; http://engineering.utsa.edu/~yfhuang/; (210) 458-6270; E-mail subject: CTA Postdoc.
Minimum Requirements: Ph.D. in Electrical Engineering, Computer Science, Statistics, or related areas. US citizenship is not required but will be given priority.
Preferred Qualifications: Strong statistical learning skills with experience in design, analysis, and statistical signal processing/machine learning applied to data from complex experimental designs.
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