Thesis Work - AI-Assisted Design and FEM-Based Development of a Spherical Electrical Machine for Robotic Actuation

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This role sits within ABB's Robotics business, a leading global robotics company. We're entering an exciting new chapter as we’ve announced the plan for SoftBank Group to acquire ABB Robotics. SoftBank is a globally recognized technology group and investor/operator focused on AI, robotics, and next-generation computing.  By joining us now, you’ll be part of a pioneering team shaping the future of robotics—working alongside world-class experts in a fast-moving, innovation-driven environment.

This Position reports to:

AI-Assisted Design and FEM-Based Development of a Spherical Electrical Machine for Robotic Actuation

Future robotic systems require actuators that combine high torque density, compact dimensions, low weight, and multiple degrees of freedom. Spherical electrical machines represent a promising alternative to conventional rotary actuators by enabling direct generation of torque in several directions within a single electromechanical device. However, their complex three-dimensional geometry and electromagnetic behavior present significant design and simulation challenges.

This thesis will investigate the design and analysis of a spherical electrical machine intended for a robotic joint application subject to specific space and mass constraints. The machine topology may be based on either a permanent-magnet or induction-machine concept. The winding arrangement will build upon previous research conducted at KTH, serving as a foundation for the development of a new machine design adapted to the target application.

Details:

• Period: January 2027 to June 2027
• Number of credits:  30 ECTS/högskolepoäng (hp)
• Number of students for this thesis work: 1
• Location: ABB Robotics Sweden AB, Västerås

A central objective of the project is the creation of a fully parametric design and simulation workflow using open-source tools. The student will develop software routines for geometry generation, meshing, model parametrization, and automated three-dimensional finite-element analysis using Elmer FEM. Particular emphasis will be placed on the use of modern AI-assisted code generation tools to accelerate software development and model implementation. The resulting framework should enable rapid evaluation of design variants and support the electromagnetic optimization of the machine.

The work combines electrical machine design, finite-element modelling, scientific computing, and artificial intelligence-assisted engineering methods, offering the student experience in both advanced electromagnetic design and emerging AI-driven engineering workflows.

The thesis is suitable for highly motivated M.Sc. students with an interest in electrical machines, electromagnetics, robotics, and computational engineering. Applicants from the following programs are particularly encouraged to apply:

• Electric Power Engineering
• Engineering Physics
• Systems, Control and Robotics
• Mechatronics
• Applied Mathematics and Computational Science
• Computational Engineering
• Embedded Systems (with strong interest in modeling and simulation)

The ideal candidate has a solid background in electromagnetics, electrical machines, or numerical methods, and is interested in finite-element analysis, scientific programming, and AI-assisted engineering workflows. Experience with Python, Matlab, FEM software, or CAD tools is advantageous but not required.

Recruiting Manager LiWei Qi, +46 73 021 2309, will answer your questions.

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
Please note that this position is part of our talent pipeline and not an active job opening at this time. By applying, you express your interest in future career opportunities with ABB.

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