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relationship to the performance of Army Systems; to create physically correct models that support the generation of realistic scenes of targets, terrain environments, cultural features, and battle damage; and to
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-relevant compounds (MRC) currently under research, development, testing, and evaluation (RDT&E). Safeguarding the health and welfare of service members, civilians, and the environment requires an assessment
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environment. Strong attention to detail, with the ability to strictly adhere to established safety, nursery, and plant propagation protocols without deviation. Dependable and able to follow clear instructions
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and oral communication skills. Ability to participate independently and in collaborative team environments. A complete application consists of: Complete Zintellect profile Complete Application questions
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Conducting research and analysis of current threat environment Learning about DTRA Test and Assessment activities Gaining experience communicating and coordinating across Agency Divisions, Departments, and
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the development and testing of advanced numerical modeling techniques to address challenges in riverine and coastal environments. This research will focus on enhancing simulation capabilities used to model compound
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to address fluid dynamics challenges in riverine and coastal environments. This research will focus on enhancing simulation capabilities used to model riverbank stability, particularly in the context
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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
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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
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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