[Eeglablist] Postdoctoral position in statistical learning, visualization and signal processing for computational neuroscience

[Kay Robbins]

*Postdoctoral position in statistical learning, visualization and signal
processing for computational neuroscience*

*Job Description*: We are seeking a 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/or visualization preferably with research experience in
neuroscience or cognitive science. The candidate will be based at
University of Texas at San Antonio (UTSA) and will work closely with
researchers and students at participating universities and will present the
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 University of
Michigan, National Chiao Tung University, and University of Osnabrück.

*Minimum Requirements*: Ph.D. in Electrical Engineering, Computer Science,
Statistics, or related area. Both beginning and more senior postdoctoral
candidates are encouraged to apply. 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.

*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; yufei.huang at utsa.edu;
http://engineering.utsa.edu/~yfhuang/; (210) 458-6270; E-mail subject: CTA
Postdoc.

The University of Texas at San Antonio is an Equal Opportunity/Affirmative
Action Employer. As part of the application process, applicants will be
invited to complete an online confidential and voluntary self-disclosure
card.
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