Machine Learning Algorithms for Brain Computer Int
at ORAU Workforce Solutions

Date Posted: 12/23/2018

Opportunity Description

The Army Research Laboratory (ARL) has a research opportunity available in the research and development of brain-computer interaction technologies (BCIT). Specifically, ARL is looking for an outstanding individual to advance development of machine learning and classification techniques for increasing the robustness of Army-relevant BCIT. A successful candidate will have expertise in one or more of the following areas: statistical classification and machine learning methods, semisupervised graphical learning, analysis of large-scale data sets, advanced signal processing, multivariate statistics, computer programming, experimental design, EEG, and physiological recording and analysis. Emphasis will be on translational research and technology development that will leverage years of research. Candidate will support the short-term goal (5 years) of developing a working proof-of-concept system that demonstrates the viability BCITs in operational environments. The candidate will analyze data, perform system development, publish papers, and integrate ideas and methods with the ongoing efforts of a multidisciplinary research team. Reference: Wu, D., Lance, B. J., Parsons, T. D. (2013). Collaborative Filtering for Brain-Computer Interaction using Transfer Learning and Active Class Selection. Public Library of Science – One (PLoS-ONE). Vol. 8, No. 2. Lance, B., Kerick, S., Ries, A., Oie, K., McDowell, K. (2012). Brain-Computer Interface Technologies in the Coming Decades. Special Centennial Issue of the Proceedings of the IEEE. Vol. 100, No. 13, pp. 1585-1599. and Active Class Selection. Public Library of Science – One (PLoS-ONE). Vol. 8, No. 2. Click here for more information

Opportunity Snapshot

About Us

Oak Ridge Associated Universities (ORAU) administers Science, Technology, Engineering and Mathematics (STEM) research participation programs for civilians such as:

The U.S. Army Research Laboratory (ARL) Research Associateship Program (RAP) allow Postdoctoral Fellows, Journeyman Fellows (undergraduate and graduates students and recent graduates), Senior Researchers, and Summer Faculty engage in research initiatives of their own choice, that are compatible with the interests of the government and will potentially contribute to the general effort of the ARL. Scientists and engineers at ARL help shape and execute the Army's program for meeting the challenge of developing technologies that will support Army forces in meeting future operational needs.

Research opportunities include, but are not limited to the following disciplines: Aerospace Engineering, Anthropology, Archeology, Biology, Biochemistry, Biological Engineering, Biomechanical Engineering, Biomedical Engineering, Chemical Engineering, Chemistry, Computer Science, Computer Engineering, Electrical Engineering, Environmental Health Risk Assessment, Environmental Science, Entomology, Epidemiology, Ergonomics, Geology, Health Education Mechanical Engineering, Materials Science, Mathematics, Nanotechnology, Photonics, Physics, Public Health Economics, Public Health Policy, and more.

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