Stage – Optimisation intelligente de la performance et de l’énergie sur STM32 – F/H
Core
Develop adaptive optimization methods for high-performance STM32 microcontrollers by comparing classical algorithmic approaches with machine learning techniques to analyze electrical process characteristics.
Role type
Embedded systems engineering intern (ML & optimization)
Builds
Test and validation chains for new product development
Domain
Semiconductor / Embedded systems / Machine learning
Deliverable
production ML models
Required skills
Embedded systems, Machine learning, Statistical analysis, Test design, Data analysis, Algorithmic optimization
Responsibilities
Explore state-of-the-art techniques for power supply and transistor bias optimization; Define key performance indicators; Design and implement test and validation chains; Analyze results and provide statistical interpretation; Write a synthesis report with recommendations.
