The University of Texas at San Antonio is 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). Requirements: The ideal candidate will have a strong background in machine learning, computer brain interfaces, and computer programming as well as experience in applying computational tools to large-scale problems in neuroscience. Minimum Requirements: Ph.D. with research experience in machine learning and computational approaches to data analysis. Preferred Qualifications: Strong skills in statistical learning with experience applied to data from complex experimental designs especially in neuroscience such as EEG data; experience in Brain Computer Interface. The candidate should have a PhD in a discipline related to these requirements. For details, please see the job description at IEEE jobsite.