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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.

 

UTSA is an equal opportunity employer.

 

For additional information please contact:

Professor Yufei Huang

Department of Electrical and Computer Engineering

University of Texas at San Antonio

One UTSA Circle

San Antonio, TX 78249

210-458-6270

Yufei.huang@utsa.edu

 
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