Engineer/Scientist Fellowship: Sensor Modeling and Distributed Systems State Estimation
Not specified
No deadline
United States
individual
About This Opportunity
The Army Research Laboratory Research Associateship Program (ARL-RAP) offers a fellowship opportunity for an engineering research scientist/engineer to research continuous monitoring of Soldier variability for continuously adaptive technologies. This position focuses on developing novel theories, experiments, and hardware solutions for modeling and measuring individual sensors across a deformable, distributed frame (e.g., a human) that are part of a distributed heterogeneous sensor system. The fellow will work to remove individual sensor-induced measurement noise and generate robust, resilient state estimates at the individual level. The fellowship involves collaboration on longitudinal human subjects research data collection, analysis, and development of novel technologies and theories. The fellow will be expected to publish first-author efforts in peer-reviewed literature, contribute technically to diverse peer-reviewed publications, and develop experimental and transition efforts. This opportunity requires a mix of skill sets including developing theories supporting distributed state estimation and validating those theories in hardware, with research conducted in Linux, ROS, Matlab, and C/C++. The ARL-RAP is designed to significantly increase the involvement of creative and highly trained scientists and engineers from academia and industry in scientific and technical areas of interest and relevance to the Army.
Who Can Apply
- Region
- United States
- Citizenship
- United States
- Project in
- United States
- Applicants
- individual
- Age
- 18 - 151 years old
- Post-degree
- Up to 6 years
Application Details
Stages
- 1 two_stage
Required documents
Review process
Applicants must first be selected by an ARL advisor, then submit a research proposal to the ARL-RAP review panel for evaluation.
Additional benefits
- mentorship
- networking
Post-award obligations
- publish_findings
- acknowledge_funder
External Application
This opportunity requires you to apply directly on the funder's website.
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Always verify on the official sourceKey Information
- Award Amount
- Not specified
- Application Deadline
- No deadline
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