Graduation: Automation of Sound level predictions

Qabird; Gorinchem; On-site; EUR 6,696 - 11,160; Full time

Benefits offered by this job

Academic level mentoring

Internship compensation

Travel allowance

Potential for publication or conference contribution

Job summary

Qabird in Gorinchem, Netherlands, is offering an internship focused on developing methods for acoustic source analysis. Intern responsibilities include modeling acoustic sources, defining characteristics such as RPM, and creating a prototype application in Python or MATLAB. Students will receive academic-level mentoring and have the opportunity for internship compensation. This role is open to international students who meet eligibility requirements, with potential to influence future digital products.

Qualifications

• Good programming/scripting skills in MATLAB or Python are essential.
• Analytical orientation and affinity with acoustics are required.
• Mastering English language is necessary for effective communication.

Responsibilities

• Create a model that classifies acoustic sources from recordings.
• Define source-specific outputs such as RPM and blades number.
• Develop a prototype application using Python or MATLAB.

Skills

Affinity with acoustics

Familiarity with signal processing

Analytical mindset

Good programming skills in MATLAB/Python

Mastery of English language

Job description

We offer you an Ocean of Possibilities. Join our family.

About us

At Damen, much effort is put into designing silent and comfortable ships. Therefore, sound level predictions are made to judge the feasibility of each design. This of course asks for accurate prediction methods.

Project Objective

Develop a method and build a tool that analyzes an audio recording from a sea trial and automatically:

• Identifies acoustic sources (diesel engine, electric motor, propeller, cavitation, turbulence, pump/HVAC, etc.).
• Determines source characteristics (rotational speed/RPM, number of blades/cylinders, etc.).
• Quantifies the acoustic contribution per source (level, spectrum, and derived metrics).
• Performs source separation (acoustic representation of the contribution of each detected source).

Key accountabilities

As an intern, you will:

• Create a model that classifies acoustic sources in a time domain recording of pressures, accelerations, etc.
• Define source‑specific output such as RPM, number of blades, and number of cylinders.
• Create a prototype application (Python/MATLAB).
• Deliver documentation and evaluation based on real Damen sea trial data.

Skills & Experience

• Affinity with acoustics such as spectrograms and harmonic analysis.
• Familiarity with signal processing and Machine Learning frameworks.
• Analytical oriented mindset.
• Good programming/scripting skills in Matlab/Python.
• Mastery of the English language (spoken and written).

What we offer

• Academic level mentoring throughout the internship.
• Internship compensation and travel allowance in line with company policy.
• A project with direct relevance to multiple business functions and future digital products.
• Potential for internal rollout, and possibly a publication or conference contribution depending on results.

Eligibility

International students without accommodation in the Netherlands are not eligible.