The board
Opportunity
Research
Postdoctoral Research Associate - Uncertainty Modeling
University System of New Hampshire
- Hours
- Full time
- Where
- University of New Hampshire – Main Campus
- Posted
- Sep 9
This postdoctoral researcher position is an essential staff role within Center for Acoustics Research and Education (CARE) supporting a federally funded Office of Naval Research (ONR) research project. This research position will investigate models and their uncertainty for underwater acoustic propagation to better estimate the spatial and temporal properties of underwater soundscapes. The successful applicant will develop physics-based and empirical models for uncertainty in acoustic propagation and validate them with existing ocean acoustic data sets. This position is fully funded for two years and will function as part of an interdisciplinary team of researchers in academia and industry.
The position requires a high level of independent research skill and technical expertise in physical oceanography, numerical modeling, acoustic propagation, and scientific computing.
What you'd do
- Develop models for uncertainty in underwater acoustic propagation that are applicable to a wide range of ocean environments. (40%)
- Lead efforts to translate propagation and uncertainty models into computationally efficient algorithms that can be executed on underwater platforms. (40%)
- Assist in the development of manuscripts, conference presentations, and technical reports to document and communicate research findings. (20%)
What they want
- A Ph.D. in applied mathematics, physics/applied physics, acoustics, or related discipline.
- Strong communication, writing, and programming skills.
- A demonstrated ability to conduct research independently and as part of a collaborative team.
- Candidate must be a US citizen.
- An interest in underwater acoustics or oceanography.
- Advanced knowledge of physical oceanography, numerical methods, or closely related principles relevant to acoustic propagation modeling.
- Proficiency in scientific programming and computational tools commonly used in numerical modeling and environmental data analysis, such as Python, MATLAB, Fortran, C/C++, or comparable languages and tools.
- Ability to work with large datasets and to integrate these data with acoustics models.
- Knowledge of model validation, uncertainty assessment, data assimilation, model initialization, downscaling, or related model-data integration approaches.
- Excellent analytical, critical-thinking, and problem-solving skills for addressing complex physical and computational research questions.
- Starts
- 2026-09-09