Acoustics, Value-added Localization with Noise
The Navy seeks data-driven signal processing techniques using vessel noise to estimate ocean properties like depth and sound speed, and develop data assimilation models.
This grant is no longer accepting proposals
NRC Research Associateship Programs has archived this opportunity.
Funder: NRC Research Associateship Programs
Due Dates: May 1, 2025 (Naval Postgraduate School opportunity)
Funding Amounts: Base stipend approximately $67,000/year plus $3,000 travel allowance; supplements based on experience; typical award duration 2-3 years.
Summary: Supports postdoctoral and senior researchers in data-driven acoustic signal processing to estimate oceanographic parameters and develop data assimilation models at the Naval Postgraduate School.
Key Information: Open to U.S. citizens, permanent residents, and non-U.S. citizens; requires PhD; relocation and health insurance benefits included.
Description
This fellowship opportunity at the Naval Postgraduate School (NPS) focuses on advancing physics-informed, passive acoustic methods to study regional oceanography. The research emphasizes data-driven, through-the-sensor signal processing techniques that utilize acoustic energy emitted by uncontrolled broadband surface vessels ("ships of opportunity"). These acoustic sources are exploited to estimate critical oceanographic parameters such as sea-floor depth, bottom characteristics, and the sound speed profile within the water column.
Near-term research goals include understanding the information content of ambient noise, identifying influential oceanographic processes, characterizing source dynamics, and optimizing sensor configurations. Long-term objectives involve developing advanced data-assimilation models, including Bayesian approaches, to improve environmental parameter estimation.
This research aligns with Navy interests in passive acoustic monitoring and environmental characterization, offering opportunities to contribute to both fundamental science and applied oceanographic modeling.
