MD and FL-Human Research & Engineering Dir-FFP, Human Research and Engineering Directorate - FFP
||Aberdeen Proving Ground, MD 210055425
To develop advanced autonomous systems, robots, and analytical tools, advances in machine learning must be coupled with improved understanding and modeling of human cognitive mechanisms and human behavior. ARL is looking for a Research Associate to further our goal of developing quantitative computational models of human behavior and neurophysiological (electroencephalography, EEG) signals during visual search. Research opportunities include experimental study of naturalistic visual search and other behavior, EEG analysis, and development of “deep” machine learning algorithms, computational models, and theory. Focus will be placed on advancing our fundamental understanding and developing predictive models of how scene dynamics affect EEG signals and visual search behavior. Ideally, candidates should demonstrate expertise in cognitive neuroscience (or a related discipline), EEG, visual search, human behavior, and/or computational modeling. All candidates must possess strong quantitative skills (e.g., Matlab, Python) and/or experience with EEG analysis software (e.g. EEGlab).
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Ries AJ, et al: The impact of task demands on fixation-related brain potentials during guided search. PLoS One 11(6): 2016, e0157260. doi: 10.1371/journal.pone.0157260