*Postdoctoral Position in data modeling and analysis of brain/body imaging*
We are seeking a highly motivated postdoctoral fellow to be part of an
interdisciplinary research alliance (Cognition and Neuroergonomics
Collaborative Research Alliances (CNACTA)) working to develop data
analysis and management methods and tools for mobile brain/body imaging
data in support of a research program in neuroergonomics (the study of
the brain and body at work). The research alliance seeks to discover
relationships between brain dynamics (recorded by non-invasive EEG) and
motivated behavior (recorded by body motion capture, eye tracking and
other sensors) in interactive, information-rich human-system operating
environments with an overall goal of developing performance enhancement
and monitoring technology.
The ideal candidate will have a strong background in computation,
machine learning, and/or visualization and have an interest in applying
computational tools to large-scale problems in neuroscience. The fellow
will be based at the University of Texas at San Antonio but will
collaborate with a group of Army-funded government and industry
researchers in gathering and analyzing data from successively more
complex and realistic experiments. The successful applicant will be
hired by and will work closely with the CANCTA research group at the
University of Texas at San Antonio led by Dr. Kay Robbins of Computer
Science and Dr. Yufei Huang of Electrical and Computer Engineering. The
fellow will also interact with partner groups at UC San Diego,
University of Michigan, Columbia University, University of Osnabrück,
and National Chiao Tung University. In addition to participating in this
unique large-scale analysis project, the fellow will present the
research at conferences and in the open research literature.
Salaries will be competitive. Transitions to permanent government or
industry research positions may be available for successful candidates.
*Minimum Requirements*: Ph.D. with research experience in machine
learning and computational approaches to data analysis. It is preferred
that the candidate is an American citizen or Permanent resident.
*Preferred Qualifications*: Strong skills in statistical learning with
experience applied to data from complex experimental designs especially
in neuroscience such as EEG data.
For additional information please contact:
Professor Yufei Huang
*Email: Yufei.huang(a)utsa.edu <mailto:Yufei.huang@utsa.edu>*
Department of Electrical and Computer Engineering
University of Texas at San Antonio
One UTSA Circle
San Antonio, TX 78249
210-458-6270 <tel:210-458-6270>
The University of Texas at San Antonio is an Affirmative Action/Equal
Opportunity Employer. Women, minorities, veterans, and individuals with
disabilities are encouraged to apply.
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