PhD on Identification of material properties in complex magnetic systems

PhD on Identification of material properties in complex magnetic systems

Published Deadline Location
28 Sep 17 Dec Eindhoven

Job description

The Electromechanics and Power Electronics (EPE) group at the Electrical Engineering (EE) department of TU/e has an open position for a PhD student on the Identification of material properties in complex magnetic systems. This project aims to combine measurements and advanced computational techniques to develop a novel methodology for accurately determining the magnetic properties of materials used in the manufacturing of electrical machines.

Goal and background

The increasing demand for highly efficient electrical machines and the scarcity of rare earth materials necessitates the development of soft magnetic materials that perform exceptionally well. Accurate identification of magnetic properties of processed magnetic material, such as stacked laminations, geometries made from soft magnetic composites (SMC) or 3D printed magnetic materials, is crucial, not only during the design routines, but also for optimising the manufacturing process itself. Accurate estimation of magnetic losses, for instance, is a complicated task as these losses are governed by electromagnetic phenomena, such as hysteresis and eddy currents, which are further influenced by manufacturing effects. This research project aims to develop methods which will enable accurate characterization of magnetic material which has been used to manufacture complex magnetic structures such as ones used in electric machines, transformers, and various types of actuators.

Research challenges

The research will focus on both, numerical techniques, to develop the characterization methodologies, and measurements, to experimentally validate the newly developed concepts. Numerical techniques could include development of two- and three-dimensional finite element formulations and their implementations, machine learning techniques, such as physics informed neural networks or Finite Element - based Neural Networks, used to identify material properties from measurement data.

The challenges are to identify the deterministic components of the problem such as geometry, dominant disturbances from the environment and main physical processes, formulate them numerically and use identification methods to finalize with the material characterization.


PhD student

Work environment

Eindhoven University of Technology (TU/e) is a young university, founded in 1956 by industry, local government, and academia. Today, their spirit of collaboration is still at the heart of the university community. We foster an open culture where everyone feels free to exchange ideas and take initiatives.

Eindhoven University of Technology offers academic education that is driven by fundamental and applied research. Our educational philosophy is based on personal attention and room for individual ambitions and talents. Our research meets the highest international standards of quality. We push the limits of science, which puts us at the forefront of rapidly emerging areas of research.

Eindhoven University of Technology combines scientific curiosity with a hands-on mentality. Fundamental knowledge enables us to design solutions for the highly complex problems of today and tomorrow. We understand things by making them and we make things by understanding them.

Our campus is in the centre of one of the most powerful technology hubs in the world: Brainport Eindhoven. Globally, we stand out when it comes to collaborating with advanced industries. Together with other institutions, we form a thriving ecosystem with one common aim - to improve quality of life through sustainable innovations.

The Electromechanics and Power Electronics group is one of the nine research groups of the Department of Electrical Engineering at TU/e. The group is the main center for research in electromechanical power conversion and power electronics in the Netherlands. The research is aligned with the three main strategic research themes of the Eindhoven University of Technology, i.e., Energy, Health and Smart Mobility. The four research tracks of the EPE group are high-tech motion systems and robotics, power electronics systems, smart mobility and advanced modeling. Furthermore, the group is one of the founders of the High Tech Systems Center in which all mechatronic knowledge of the TU/e will be bundled.


Eindhoven University of Technology (TU/e)


The PhD student for this research project should fulfil the following requirements:
  • MSc degree in Electrical and/or Power Engineering, Applied Mathematics, or Applied Physics
  • Successful candidates should have at least one (preferably two) of these crucial for this project skills:
  • Experience with Finite Element formulations and their implementation, preferably in the domain of magnetics domain.
  • Experience with machine learning tools, both theoretical and practical (familiarity with python tools such as TensorFlow and PyTorch) are welcome.
  • Knowledge about the science behind magnetic materials, losses mechanisms, hysteretic and eddy currents behaviour. Experience, with magnetic measurement setups such as Epstein frames, design, and automation of magnetic measurements to collect data.

  • Strong analytical and research skills
  • Excellent communication skills
  • Ability to independently organize his/her own work, to solve problems, to achieve desirable goals and to cooperate
  • Project management skills are a plus
  • Ability to participate in the teaching process in BSc and MSc programs (both taught in English)
  • Good scientific writing and documentation skills
  • Strong command of the English language (knowledge of Dutch/German language is a plus)

Conditions of employment

A meaningful job in a dynamic and ambitious university, in an interdisciplinary setting and within an international network. You will work on a beautiful, green campus within walking distance of the central train station. In addition, we offer you:
  • Full-time employment for four years, with an intermediate evaluation (go/no-go) after nine months. You will spend 10% of your employment on teaching tasks.
  • Salary and benefits (such as a pension scheme, paid pregnancy and maternity leave, partially paid parental leave) in accordance with the Collective Labour Agreement for Dutch Universities, scale P (min. €2,770 max. €3,539).
  • A year-end bonus of 8.3% and annual vacation pay of 8%.
  • High-quality training programs and other support to grow into a self-aware, autonomous scientific researcher. At TU/e we challenge you to take charge of your own learning process.
  • An excellent technical infrastructure, on-campus children's day care and sports facilities.
  • An allowance for commuting, working from home and internet costs.
  • A Staff Immigration Team and a tax compensation scheme (the 30% facility) for international candidates.

Additional information

About us

Eindhoven University of Technology is an internationally top-ranking university in the Netherlands that combines scientific curiosity with a hands-on attitude. Our spirit of collaboration translates into an open culture and a top-five position in collaborating with advanced industries. Fundamental knowledge enables us to design solutions for the highly complex problems of today and tomorrow. 


Do you recognize yourself in this profile and would you like to know more?
Please contact the hiring manager dr. M; Curti, m.curti[at]

Visit our website for more information about the application process or the conditions of employment. You can also contact

Are you inspired and would like to know more about working at TU/e? Please visit our career page.


We invite you to submit a complete application by using the apply button.
The application should include a:
  • Cover letter in which you describe your motivation and qualifications for the position.
  • Curriculum vitae, including a list of your publications and the contact information of three references.

We look forward to receiving your application and will screen it as soon as possible. The vacancy will remain open until the position is filled.


  • PhD
  • Engineering
  • max. 38 hours per week
  • University graduate
  • V36.6949


Eindhoven University of Technology (TU/e)

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De Rondom 70, 5612 AP, Eindhoven

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Application procedure

Application procedure

Make sure to apply no later than 17 Dec 2023 23:59 (Europe/Amsterdam).