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Master Thesis in Machine Learning Pipeline for PartType Detection in Industrial Production Processes

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Company Description

At Bosch, we shape the future by inventing high-quality technologies and services that spark enthusiasm and enrich people’s lives. Our promise to our associates is rock-solid: we grow together, we enjoy our work, and we inspire each other. Join in and feel the difference.

The Robert Bosch GmbHis looking forward to your application!

Job Description

  • During your assignment, you will implement a full machine learning pipeline in Python for classification and clustering of real machine processing data.
  • You will research and apply feature extraction for multivariate time series data.
  • Furthermore, you will research, apply and evaluate different time series classification and clustering methods for machine processing data.
  • Last but not least, you will explore the applicability of semi-supervised representation learning of time series for classification and clustering tasks.


  • Education: studies in the field of Computer Science, Physics, Engineering, Informatics or comparable
  • Experience and Knowledge: in Software development, Machine Learning, Programming and in Python
  • Personality and Working Practice: independent, team-minded and curious
  • Languages: good in English or German

Additional Information

Start: according to prior agreement
Duration: 6 months

Requirement for this thesis is the enrollment at university. Please attach your CV, transcript of records, examination regulations and if indicated a valid work and residence permit.

Diversity and inclusion are not just trends for us but are firmly anchored in our corporate culture. Therefore, we welcome all applications, regardless of gender, age, disability, religion, ethnic origin or sexual identity.

Need further information about the job?
Sebastian Becker (Functional Department)
+49 711 811 54463 



  • Type: Full-time
  • Function: Research
Nach Absprache

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