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Opportunity at Davies Teaching Fellowships (ARL/USMA)

Machine Learning Algorithms for Brain Computer Interaction


MD and FL-Human Research & Engineering Dir-FFP, Human Research and Engineering Directorate - FFP

RO# Location
AA.27.01.B7846 Aberdeen Proving Ground, MD 210055425


Name E-mail Phone
Lance, Brent Jason 410 278 5943


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, deep 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. The Associate will support the short-term goal (five years) of developing a working proof-of-concept system that demonstrates the viability BCITs in operational environments. The Associate will analyze data, perform system development, publish papers, and integrate ideas and methods with the ongoing efforts of a multidisciplinary research team.



Saproo S, et al: Cortically coupled computing: A new paradigm for synergistic human-machine interaction. Computer 49(9): pp.60-68, 2016

Lance BJ, et al: Towards Serious Games for Improved BCI. Handbook of Digital Games and Entertainment Technologies: 197-224, 2017

Lance B, et al: Special Centennial Issue of the Proceedings of the IEEE 100(13): 1585, 2012 and Active Class Selection. Public Library of Science–One (PLoS-ONE) (8)2: 2012


Brain-computer interaction; Neuroscience; Machine learning; EEG;


Citizenship:  Open to U.S. citizens
Level:  Open to Postdoctoral applicants
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