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Your Role
This MSc thesis focuses on FMCW radar sensing, signal processing, and lightweight AI algorithms for monitoring operating states of home appliances.
Key responsibilities in your new role
- Shape the future: Design and implement the radar DSP pipeline end to end – sensor characterization and calibration, range/Doppler processing, clutter suppression, beam forming, feature extraction, and lightweight ML algorithms and neural networks
- Keep the overview: The work includes algorithm and model development, benchmarking, documentation, and presenting results to technical stakeholders, with the opportunity to prototype deployment on embedded platforms
Your Profile
Qualifications and skills to help you succeed
- Study field: You are currently a master’s student in Electrical Engineering, Computer Science, Physics, Applied Mathematics, or related, at thesis stage
- Experience & Interest: Strong background in DSP and radar systems (FMCW preferred), including FFT-based processing, filtering/windowing, and beamforming
- Skills: Proficient in Python; experience with AI algorithms applied to sensor data (lightweight models preferred) & common ML/DSP libraries
- Language: Good skills in English; German is a plus
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
Contact:
Mafalda Porto
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