MD and FL-Human Research & Engineering Dir-FFP, Human Research and Engineering Directorate - FFP
||Aberdeen Proving Ground, MD 210055425
With headquarters in Adelphi, Maryland, the US Army Research Laboratory (ARL) is the nation's premier laboratory for land forces. Its diverse assortment of unique facilities and dedicated workforce of government, academic, and private sector partners make up the largest source of world-class integrated science and technology in the Army.
Basic science research is needed to address critical knowledge gaps underlying efforts to seamlessly integrate humans and advanced technology for future military and civilian applications. Broad needs defined within this problem space demand high-quality, complex experimentation combined with advanced quantitative analysis and modeling of human brain-body states and their dynamics in simulated and actual (real-world) operational contexts. This pursuit is inherently multidisciplinary, leveraging information available within and across levels from individual psychophysiology to overt cognitive performance and behavior. The current project aims to understand sources of individual variability in decision-making and performance of human-automation and human-human teams during military and civilian vehicle operation. Therefore, exceptional postdoctoral candidates should function well on diverse, multidisciplinary teams and themselves be well-versed and proficient in at least two of the three following general domains, including: (1) analysis of human behavior and performance, (2) bioinformatics or computational modeling, and (3) engineering. Research activities will involve developing experimental protocols, obtaining and maintaining IRB approval, management and execution of human subjects research at US military installations, managing and analyzing data, and authoring presentations and manuscripts for peer-review publication or government technical reports.
Applicants must have earned a doctoral degree (PhD) in Cognitive Science, Psychology, Neuroscience, Biomedical Engineering, Human Factors, or a closely related discipline. A strong preference is accorded to candidates capable of independent, end-to-end data analysis including acquisition, signal conditioning and data reduction, visualization, and statistical analysis and/or quantitative modeling. Substantial high-level programming experience (i.e., MATLAB, Python, C/C++, R), is heavily preferred. Candidates should demonstrate a strong scientific background with examples of recent high-quality first-author presentations and writing. Strong candidates will have already successfully published (or had work accepted for publication) in one or more peer-reviewed journals.
Drnec K, Marathe AR, Lukos JR, Metcalfe JS: From trust in automation to decision neuroscience: Applying cognitive neuroscience methods to understand and improve interaction decisions involved in human automation interaction. Frontiers in Human Neuroscience 10. DOI: 10.3389/fnhum.2016.00290, 2016
McDowell K, et al: Real-world neuroimaging technologies. IEEE Access 1. DOI: 10.1109/ACCESS.2013.2260791, 2013
Human performance; Joint cognitive systems; Trust in automation; Human-automation interaction; Psychophysiology; Human state estimation; Decision-making; Military research; Real-world neuroscience;