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

Location

Villach

Entry level

0-1 year

Job ID

39412

Start

immediately

Type

Full time

Contract

Temporary

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)

Profile

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

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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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