ABB

MSc Thesis Work for: Understanding Tonal Noise in Permanent Magnet Machines

Sweden · Work style not stated

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About the role

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EmployerABB
LocationSweden
Work styleWork style not stated
Employer posted2 Oct 2026

At ABB, we help industries outrun - leaner and cleaner. Here, progress is an expectation - for you, your team, and the world. As a global market leader, we’ll give you what you need to make it happen. It won’t always be easy, growing takes grit. But at ABB, you’ll never run alone. Run what runs the world.

This Position reports to:

R&D Team Lead

Details:

· Period:Start Jan-June 2027

· 30 ECTS per student

· Number of students: 1

· Location: ABB Corporate Research in Västerås, Sweden

You will be part of Materials Technology & Electromagnetics team at ABB Corporate Research in Västerås, Sweden. At Corporate Research we lead the innovation within ABB and our task is to ensure ABB's technology competitiveness now and in the future. We work in close collaboration with other research centers, our business areas: Motion, Automation and Electrification, as well academic and industrial partners. In our creative and highly skilled team we develop, design, build and test new concepts and prototypes of physical and digital powertrains or electrical devices.

Show full description

The increasing use of electric machines has made tonal noise an important e‑NVH challenge. In Interior Permanent Magnet (IPM) machines, tonal noise is mainly driven by electromagnetic force harmonics, structural resonances, and their interaction with the acoustic response.

This thesis aims to improve the understanding of tonal noise generation in IPM machines using simulation and measurement data. The work will focus on identifying the key e-NVH features related to tonal noise.

Your role and responsibilities

Conduct a literature review of existing methods for e‑NVH and tonal-noise analysis.
Work with simulation and measurement e-NVH data.
Apply signal-processing techniques to identify relevant noise features.
Explore data-analysis and machine-learning methods for tonal-noise prediction
Identify the key factors governing tonal-noise generation and assess their relative importance.

Qualifications for the role

Master of Science student in Mechanical Engineering, Engineering Physics, Computer Science, or a related field.
Good understanding of signal processing concepts, such as FFT and frequency-domain analysis.
Programming and data-analysis skills; prior experience with machine learning is an advantage.
Basic knowledge of electric machines is beneficial.
Willingness to learn how to use Multiphysics simulation tools.

More about us

Recruiting Manager David Lindell , 46 72 461 35 03, will answer your questions. Main contacts:

Binaya Baidar, binaya.baidar@se.abb.com;

Jiaojiao Song, jiaojiao.song@se.abb.com

Positions are filled continuously. Please apply with your CV, academic transcripts, and a cover letter in English.

We look forward to receiving your application!

A future opportunity

This role is part of our talent pipeline, which means it’s not currently open, but we’re always looking for curious minds, bold thinkers, and people who want to make an impact.

Click Apply to express your interest and be considered for future opportunities that match your experience and aspirations.

At ABB, we welcome people from all backgrounds and believe that diverse perspectives help us build a cleaner, smarter future.

Apply today or visit https://www.abb.com to learn more about how we help run what runs the world.

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