Unlock the Power of Transfer Learning for Time Series Classification

vor 3 Wochen

Erlangen, Bayern, Deutschland Siemens AG Vollzeit

Mode of Employment: Limited

Transform Your Knowledge into Innovative Solutions

Siemens AG is seeking a highly motivated and skilled individual to complete their master's thesis with us. This opportunity will enable you to combine your knowledge with our expertise, discover new connections, and formulate innovative ideas. By joining our team, you will gain a comprehensive understanding of various departments and processes, and have the chance to break new ground in the future of electrification, automation, and digitalization.

Your Key Responsibilities:

  • Explore and implement transfer learning techniques for on-site training time series classification.
  • Develop an algorithm that can adapt to new data autonomously when deployed in the field.
  • Identify the most hardware-efficient alternative combining tinyML techniques for implementation on microcontrollers or AI-accelerators.
  • Integrate the solution to create real-world impact in an industrial application, showcasing its capabilities and demonstrating on-site model updates.

Requirements:

  • Proficiency in Python for developing machine learning models and implementing algorithms.
  • Experience in C++ for implementing efficient and robust software solutions on embedded systems or AI accelerators.
  • Strong background in machine learning, particularly in transfer learning and time series data analysis.
  • Familiarity with data preprocessing, feature extraction, and concept drift detection techniques.
  • Ability to integrate and test software on hardware platforms, ensuring efficient real-time performance.

Join Our Exciting World at Siemens

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