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Master Thesis in AI-based Anomaly Detection for E-machine Test Benches
Renningen
Aktualität: 06.12.2024

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06.12.2024, Bosch-Gruppe
Renningen
Master Thesis in AI-based Anomaly Detection for E-machine Test Benches
Aufgaben:
During your thesis you will investigate and compare different AI-based approaches for the detection of anomalies in time series data on endurance test benches for e-machines. You will select and implement a suitable model. Furthermore, you will optimize and adapt the model to detect the anomalies on the real test bench. Finally, you will evaluate it based on test data or optionally in operation.
Qualifikationen:
Education: Master studies in Computer Science, Data Science, Artificial Intelligence, (Applied) Mathematics, Physics, Automation Technology, Cybernetics, Automotive Engineering, Electrical Engineering or comparable Experience and Knowledge: in the fields of data-based modeling and machine learning (ML); with common AI libraries such as PyTorch or Tensorflow; good programming skills (preferably in Python); basic knowledge in electrical engineering and electrical drive technology is an advantage Personality and Working Practice: you work independently, follow systematic approaches to tasks, and consistently deliver reliable results Languages: good in English or German

Berufsfeld

Bundesland

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Master Thesis in AI-based Anomaly Detection for E-machine Test Benches

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