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Opportunity at Davies Teaching Fellowships (ARL/USMA)

Quantifying and Predicting Brain-Body State Changes During Human-Intelligent Agent Teaming


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

RO# Location
AA.27.01.B8496 Aberdeen Proving Ground, MD 210055425


Name E-mail Phone
Metcalfe, Jason Scott 410.278.9229


With headquarters in Adelphi, Maryland, the US Army Research Laboratory (ARL) is the corporate laboratory of the US Army with a mission to conduct fundamental and applied research and transition technologies that serve our nation's Soliders. 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 intelligent agents for future military and civilian applications. Broad needs defined in 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 physiology to overt cognitive performance and behavior. The current project aims to understand decision-making and performance of human-automation and human-human teams during military and civilian mobile operations.

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 conceiving novel research, developing experimental protocols, obtaining and maintaining IRB approval, managing and executing human subjects research at US military installations, managing and analyzing data, and authoring presentations and manuscripts for peer-review publication and/or government technical reports.

Applicants must have earned (or be near completion of) 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, rigorous, 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.



DeCostanza, A.H. et al. Enhancing human-agent teaming with individualized, adaptive technologies: A discussion of critical scientific questions. US Army Research Laboratory Technical Report #ARL-TR-8359. 2018 (May). Interactive Paper available at:

Marathe, A.R., Metcalfe, J.S., et al.: The privileged sensing framework: A principled approach to improved human-autonomy integration. Theoretical Issues in Ergonomics Science, 19(3), 283-320. DOI: 10.1080/1463922X.2017.1297865, 2018.

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 

Human-automation interaction; Human-intelligent agent teaming; Human state estimation; Joint cognitive systems; Risky decision-making; Trust in automation; Real-world neuroscience; Military research; Human performance


Citizenship:  Open to U.S. citizens, permanent residents and non-U.S. citizens
Level:  Open to Postdoctoral applicants
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