
Internship - Analog-Mixed Signal Architect Support for Automotive Microcontroll (f/m/div)
Infineon Technologies Austria AGKI-Zusammenfassung
#WeAreIn to create tiny chips and big careers. Are you ready to take the first step in your career? Let's shape the future together! Whether you join as a student, intern, or trainee, you'll be part of something real - real projects, real impact, and real opportunities to grow. Are you in?
- Hands-on Experience: Gain valuable insights on the latest automotive microcontroller development and in the power management of state-of-the-art microcontrollers
- Circuit and Systems Analysis: Analyze, model, simulate or measure analog mixed-signal circuits and systems (i.e. power converters, ADCs, oscillators, power management systems)
- Power Consumption Analysis: Investigate, apply and develop innovative methods to analyze power consumption of analog-mixed signal systems
- Data Processing: Perform data acquisition and post-processing, integrating AI/ML-driven solutions to enhance automation and efficiency in Electronic Design Automation (EDA) workflows and to identify optimization opportunities.
- Thesis Option: Possibility to align the work with a Bachelor or Master thesis
Type of employment: Temporary / Part-time / Full-time (flexible working hours from Monday to Friday between 6 a.m. and 7 p.m.) Duration: min 12 months
Education: Motivated and committed student from Electrical or Electronic Engineering, Embedded Systems, Computer Science, Information Technology or similar.
Technical Skills: Solid understanding of basic electronic design, integrated circuit architecture, power electronics and digital signal processing chains, plus basic knowledge of artificial intelligence, machine learning and big data algorithms
Tools and Coding: Familiarity with simulation tools and methodologies for integrated circuit validation, basic programming skills in Matlab and Python and in register transfer level (RTL) oriented description languages such as VHDL and SystemVerilog and familiarity with artificial intelligence and machine learning frameworks
Working Style: Flexibility, good time management and a genuine interest in learning new topics as well as the ability to work effectively across other departments
Language Skills: Fluent in English, German is a plus
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