We are looking for a highly motivated AI Scientist to join an innovative research project focused on physics-informed machine learning for underwater acoustic imaging. You will contribute to the development of next‑generation AI models for sonar signal analysis, combining state‑of‑the‑art machine learning with deep expertise in signal processing and physical modelling.
The project focuses on automatically detecting and classifying mine‑like objects on the seafloor using high‑resolution Synthetic Aperture Sonar (SAS) imagery. The goal is to support mine countermeasure operations by reducing operator workload and improving detection reliability in complex and noisy underwater environments. The work includes collaboration with research institutions and focuses on bridging applied research and operational deployment.
Your role
Design and implement advanced signal and image processing algorithms for sonar data
Develop, train, and optimize machine learning models for detection and classification tasks
Work with Synthetic Aperture Sonar (SAS) datasets, including real and synthetic data
Evaluate model performance under realistic, noisy, and constrained operational conditions
Contribute to experimental validation, benchmarking, and performance analysis
Collaborate closely with domain experts and academic partners
Your profile
Required Qualifications
MSc or PhD in Applied Mathematics, Physics, Engineering, or a related field
Strong interest in AI and signal processing (e.g., time‑frequency analysis, filtering, spectral methods)
Experience with machine learning frameworks (preferably PyTorch) and strong Python programming skills
Analytical mindset with a research‑oriented approach
Motivation to develop robust systems used in real‑world operational environments
Nice to have
Experience with acoustic signal processing or coherent sensing systems (e.g., radar, sonar, medical imaging)
Knowledge of physics‑informed neural networks or complex‑valued neural networks
Familiarity with explainable AI techniques
What We Offer
Competitive salary
Electric company car with charging card
Group insurance
Hospitalization insurance with outpatient medical and dental coverage
Meal vouchers
Mobile phone subscription
12 additional RTT days (full‑time employment)
40 remote working days per year
Modern and comfortable working environment
Training and career development opportunities
A stable employer with long‑term vision
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