Sort by
Refine Your Search
-
between various system and network architectural layers and relationships between respective protocol capabilities and characteristics, as well as networking analysis and/or decision analytic tools and
-
performed in collaboration with other computational and experimental teams within ARL and academia. Qualified candidates should be US Citizens and have received their PhD in Materials Science, Mechanical
-
solutions based on an examination of the problem presented and the current state of the art in various technologies. The successful applicant will have a PhD in Physics or a related discipline with an excess
-
propagation and/or imaging in complex battlefield environments. As signals propagate through the environment, they undergo effects due to atmospheric turbulence, atmospheric gradients, terrain, and other
-
. Experimental approaches focus on developing and utilizing novel technology platforms to examine new multi-sensor combinations and critical issues of multisensory integration in real-world environments. We aim
-
the effects of the environment on biological and other aerosols. The development of modeling capabilities for such problems is an aspect of these opportunities. ARL Advisor: Steven Hill ARL Advisor Email
-
, technology, and analysis to enable full-spectrum operations. The opportunity available is in the Battlefield Environment Division of the Computational and Information Sciences Directorate (CISD). For further
-
applying these skills to characterize human behavior in real-world environments. ARL Advisor: Amar Marathe ARL Advisor Email: amar.marathe.civ@mail.mil About HRED The Human Research and Engineering
-
the ARL S&T Campaign in the Sciences-for-Lethality with research efforts related to desired effects at standoff ranges for moving targets in access denied environments to improve the performance of future
-
into Soldier teams and move from tools to teammates. Critical to this is an understanding of how humans and human teams perform and change in dynamic environments and situations. HRED leverages human-robot