Hydrodynamic Acoustic Signature Engineer

We are expanding our Underwater Acoustics R&D team with a Hydrodynamic Acoustic Signature Engineer who is motivated to contribute to our acoustic intelligence capabilities by developing hydrodynamic, acoustic, and mechanical noise models.

Optics11 is a deep-tech company developing advanced fiber-optic sensing technologies for demanding applications in underwater acoustics, offshore energy, and defense. Our novel fiber-optic technology is redefining underwater security by enabling next-generation sonar solutions to protect critical naval assets and underwater infrastructure.

You will bridge first-principles physics and data-driven methods to support the development of classification and identification pipelines by linking acoustic signatures to identifiable target characteristics. Your expertise will contribute to threat spectrum definition and realistic operational scenarios. This is expected to be achieved by the development and maintenance of a deep physics-based understanding and models of underwater acoustic signatures. Working closely with experts from multiple disciplines, you will help develop technologies that operate in some of the world's most challenging environments.

Key Responsibilities

Hydrodynamics, Underwater Acoustic Emission and Signature Modelling:

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Model hydrodynamic and mechanical noise generation mechanism of targets of interests, e.g., flow noise, cavitation, coupled structural vibration, that result in underwater acoustic noise.

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Translate physical phenomena into acoustic emission models, i.e., passive and target strength, to be used for system performance modelling.

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Define parametrized models capturing variability across operating conditions (speed, sea state, depth, configuration).

Parameter Space & Uncertainty Definition

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Establish realistic parameter brackets for target surface/underwater kinematic parameters, e.g., speed, acceleration, maneuverability, etc., and for their related underwater acoustic signatures. This is based on physical principles and validated through experimental data.

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Quantify uncertainties and sensitivities to support robust system-level predictions.

Data Processing & Machine Learning

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Generate synthetic data or semi-synthetic datasets based on physics-informed models.

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Define meaningful features derived from first principles and the properties of generation of underwater acoustic signatures.

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Support the development of classification models ensuring that models leveraging physics-based principles, for example making use of hand-crafted features.

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Support the development of pure data-driven ML/AI models by ensuring that models learn physically plausible patterns.

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Derive physics-based explanations from data-driven ML/AI models to support stakeholders’ decisions.

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Support other data processing pipelines, such as tracking (e.g., providing credible kinematic brackets) and detection (e.g., providing physically grounded inputs for detectability analysis, including array shape effects, effective aperture, and flow-induced performance degradation).

Why Join Us?

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Join one of Europe’s most promising deep-tech scale-ups.

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Shape the future of a rapidly growing multidisciplinary R&D organization.

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Competitive salary and benefits package.

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Enjoy regular team activities and company events.

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Fresh team lunches provided3 times/ week.