Master Thesis AI Integration for Large Data Analysis, Quality Management, and Predictive Maintenance

Are you an ambitious student with a passion for Artificial Intelligence and automated systems This Master thesis offers a unique opportunity to integrate advanced AI methodologies with vast machine parameter databases directly impacting process optimization quality management and predictive maintenance.

• During your thesis you will build a pilot AI-system as primary scope. All necessary machine data is readily available guidance and assistance you will receive from our digital department and factory team. Please note for data protection reasons only Bosch private AI-Infrastructure can be used.
• You will develop AI models for the evaluation of large machine parameter databases with the core objective to optimize process parameters.
• Additionally you will monitor the machine parameters to detect deviations between different tools. This will facilitate identification of root causes for process variation ultimately leading to improved stability.
• You will uncover complex dependencies between various parameters and based on these insights develop models capable of predicting future maintenance needs.
• Finally you will utilize previous and current production data to train the AI models.

Qualifications :

• Education: Master studies in the field of Information Technology Computer Science Electronics Mathematics Physics or comparable with good grades
• Experience and Knowledge: experienced with or have at least basic programming knowledge in Python C or similar languages; relevant coursework or knowledge in data science and AI
• Personality and Working Practice: you are self-driven able to take initiative and move the project forward independently with a genuine curiosity for AI and automated systems
• Work Routine: presence at the location is required
• Languages: very good in English and German

Additional Information :

Start: according to prior agreement
Duration: 4 - 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
Stefan Zeller (Functional Department)
49 

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Remote Work :

No

Employment Type :

Full-time