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@utsa.edu
Department of Electrical and Computer Engineering
University of Texas at San Antonio
One UTSA Circle
San Antonio, TX 78249
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.