Master Thesis: Pareto-front Component Prediction using Neural Network

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Master Thesis: Pareto-front Component Prediction using Neural Network

At a glance

Machine learning/Artificial Intelligence has the potential to accelerate technological advances in leaps and bounds. The aim of this project is use machine learning to learn from Pareto-front results in the case of magnetic design, and generate component outputs without the need of going through the Pareto-front analysis, in order to reduce computation time. We are looking for a student (m/f/div)* in the field of Electrical Engineering to develop and design the neural network for such a system in order to generate information to aid power system design.

Quick info



Entry level

0-1 year

Job ID





Full time



Job description

In your new role you will be responsible for:

  • Data generation required for training ML
  • Developing new neural network to make predictions
  • Speed up Pareto-front analysis
  • Develop the interface to machine learning platforms

Duration: Temporary / full-time
Starting date: earliest 01.10.2019 (working permit for Non-EU citizens takes about 6 weeks)


You are best equipped for this task if you have:

  • Studying in Electrical Engineering with some background in programming and/or Computer science
  • MATLAB/Simulink experience
  • Experience with Python and/or other MI based language
  • Good fundamental understanding of power systems
  • Basic know-how in power electronics applications
  • Analytical skills to derive and reach balanced solutions to technical challenges
  • Ability to work goal oriented and effectively communicate throughout diverse parts of an organization
  • I ntercultural awareness
  • Fluent English skills with German skills as a plus

This position is subject to the collective agreement for workers and employees in the electrical and electronics industry. Master students receive a compensation of 2.210,-- Euro gross p.m. (full-time basis)

Please attach the following documents to your application:

  • Motivation letter
  • CV
  • Copy of your Certificate of matriculation at a university
  • Copy of your Transcript of records
  • Copy of the highest completed educational certificate (Matura certificate for Bachelor students, Bachelor certificate for Master students

About Us

Part of your life. Part of tomorrow.

We make life easier, safer and greener - with technology that achieves more, consumes less and is accessible to everyone. Microelectronics from Infineon is the key to a better future. Efficient use of energy, environmentally-friendly mobility and security in a connected world - we solve some of the most critical challenges that our society faces while taking a conscientious approach to the use of natural resources.

*The term gender in the sense of the General Equal Treatment Act (GETA) or other national legislation refers to the biological assignment to a gender group. At Infineon we are proud to embrace (gender) diversity, including female, male and diverse.

Contact Us

Julia Gabriel

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