Master Thesis - Embedded AI Algorithm for Multi-Key Sensing on Magnetic Keyboard (f/m/div)

Descrizione del lavoro:

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Your Role

Key responsibilities in your new role
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

Your Profile

Qualifications and skills to help you succeed
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 spokenPlease 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

Contact:
Mayara Fortino, LinkedIn

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