[Ieee_vis] 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.