Master Thesis - Embedded AI Algorithm for Multi-Key Sensing on Magnetic Keyboard iv)

Ingenious Technologies AG
München, Germany
5 days ago

Role details

Contract type
Permanent contract
Employment type
Part-time (≤ 32 hours)
Working hours
Regular working hours
Languages
English, German

Job location

München, Germany

Tech stack

Artificial Intelligence
Experimental Data
Hardware Platform Interface
Python
Matlab
Machine Learning
PIC Microcontroller
Information Technology

Job description

#WeAreIn to create tiny chips and big careers. The future won't wait... why should you? Join us and make a difference. 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?, In this master thesis, you will contribute to the development of an embedded AI solution for next-generation magnetic keyboard sensing. Your work will focus on solving the underdetermined multi-key sensing challenge by combining hardware understanding with advanced AI model development and deployment on embedded systems.

  • Focus on the future: Extend the existing magnetic keyboard hardware platform to enable embedded AI acceleration and enhanced sensing capabilities
  • Experience research: Identify, evaluate, and train suitable AI algorithms to address the multi-key sensing problem using experimental data
  • Data is everything: Collect and preprocess measurement data using existing hardware setups and leverage tools such as Deepcraft for model training
  • Take responsibility: Optimize and deploy the developed AI algorithm on embedded hardware, ensuring efficient execution and real-time performance
  • Reliable work: Document your methodology, implementation steps, and results in a structured thesis report, As a global leader in semiconductor solutions in power systems and IoT, Infineon enables game-changing solutions for green and efficient energy, clean and safe mobility, as well as smart and secure IoT. Together, we drive innovation and customer success, while caring for our people and empowering them to reach ambitious goals. Be a part of making life easier, safer and greener. Are you in?

Requirements

Do you have experience in Python?, You are a motivated Master's student with a strong interest in embedded systems and artificial intelligence, eager to work at the interface of hardware and machine learning.

  • Study Field: You are currently pursuing a Master's degree in Electrical Engineering, Electronics, Information Technology, Informatics, Mechatronics, or a related field
  • Skills: You have strong knowledge of microcontrollers and embedded programming in C. You are familiar with CAE tools and development environments such as MATLAB, EAGLE, and Python
  • Experience: Ideally, you have practical experience applying AI techniques in academic or project settings and are comfortable using AI agents in your daily work, especially for coding tasks. Knowledge of AI model deployment on embedded platforms is a plus
  • Interests: You are interested in embedded AI and real-time algorithm implementation
  • Way of Working: Analytical, structured, and solution-oriented, with the ability to independently drive complex technical tasks
  • Personality: Curious, innovative, and motivated to explore new approaches to challenging engineering problems
  • Language Skills: Good German and English skills, both written and spoken

Please attach the following documents to your application:

  • CV in English
  • Certificate of enrollment at university
  • Excerpt of the study regulations for the thesis (if applicable)
  • Latest grades transcript (not older than 6 months
  • High school report

About the company

Ingenious Technologies is a leading independent marketing technology provider. With the cloud-based Ingenious Enterprise platform, companies across all industries can aggregate, structure, enrich and analyse all marketing data collected. Thanks to real-time processing and a high level of automation, reliable data sets are available for clients to make agile marketing decisions.

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