Lead the development, training, and evaluation of deep learning models for undersea acoustic detection, classification, localization, and related problems using Fourier analysis or signal processing.
Locations (2)
Richland, Washington, United States
Seattle, Washington, United States
Compensation
USD $140,200.00/Yr.
Maximum Salary
USD $228,800.00/Yr.
Responsibilities
Lead the development, training, and evaluation of deep learning methods for undersea acoustic detection, classification, localization, and related problems using Fourier analysis or signal processing, mathematical analysis, and experiments.
Lead research projects or major technical efforts, coordinate contributors, and plan the work, resources, and milestones.
Evaluate methods against baselines using representative data, examining detection and classification performance, false alarms, robustness to propagation and environmental variability, uncertainty, and computational demands.
Build and validate research prototypes and evaluate agentic AI systems with software and ML engineers, addressing technical barriers to transition and deployment.
Work with mission partners and domain specialists to turn user needs into research questions, and communicate findings through analyses, technical reports, and discussions.
Requirements
BS/BA
MS/MA
PhD
Nice to have: deep learning methods for undersea acoustic detection
Investigate and develop deep learning methods for undersea acoustics, analyzing acoustic data, formulating and testing algorithms, and developing, training, and evaluating deep learning models for detecting, classifying, localizing, or characterizing underwater sources and phenomena.
Locations (2)
Richland, Washington, United States
Seattle, Washington, United States
Compensation
Minimum Salary USD $114,000.00/Yr. Maximum Salary USD $182,100.00/Yr.
Responsibilities
Develop, train, and evaluate deep learning methods for undersea acoustic detection, classification, localization, separation, and related problems.
Formulate and investigate research questions through Fourier analysis, signal processing, mathematical analysis, algorithm development, and experiments.
Design reproducible experiments and compare methods, examining detection and classification performance, false alarms, robustness to propagation and environmental variability, uncertainty, and computational demands.
Analyze and interpret results, document methods and limitations, and communicate findings to project leads, collaborators, and mission partners.
Prepare research code and evaluate agentic SI systems with software and ML engineers to transition tested methods into usable tools as appropriate.
Requirements
BS/BA
MS/MA
PhD
Nice to have: deep learning methods for undersea acoustic detection
