Acoustics AI/ML Researcher

PhD in Electrical Engineering / Acoustics or related field
Experience in passive acoustic data processing and phenomenology
Experience in general signal processing and analysis
Experience with machine learning and neural networks
Strong publication record in top-tier research publications and conferences
Candidates should include a detailed list of publications as part of their resume/CV
Highly innovative and demonstrated track record for solving complex technical challenges using acoustic-generated time series or imagery
Experience collaborating successfully with others and thriving in a fast-paced and dynamic work environment
If not already cleared TS/SCI, willingness and ability to apply for and maintain a TS/SCI security clearance
Due to contractual restrictions, only US Citizens will be considered for this position

Develop robust solutions for detection, classification, anomaly detection, and soundscape analysis for both active and passive acoustic modalities in undersea and other domains
Collaborate with computer vision researchers to adapt computer vision and AI techniques to the acoustics domain
Contribute expertise in signal processing to projects outside the acoustics domain
Enjoy support and encouragement for participation in national and international conferences (such as UACE, OCEANS, OSM, IGARSS, CVPR, ICCV, and ECCV)
Be encouraged to seek funding to grow and develop your own research areas, if you desire

5+ years experience or course work in signal analysis for passive and active undersea acoustic phenomenology (e.g., Fourier analysis, complex-valued waveforms, filter design, channel estimation, detection, matched filtering, signal propagation)
5+ years experience or coursework in array signal processing techniques (e.g., beampatterns, beamforming, interference rejection, phase calibration, array design)
5+ years experience with synthetic aperture imaging techniques and data
Experience with subsea field collections