Master Thesis in Applied Machine Learning in Root Cause Pattern Identification

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 GmbH is looking forward to your application!

• During your thesis, you will conduct a comprehensive review of existing literature on 8D problem-solving methodology, AI, and ML applications in quality management.
• You will investigate current state-of-the-art ML algorithms and their applications in root cause analysis and error correction.
• Furthermore, you will analyze the current manual process used by quality engineers for defining actions, root cause analysis, and error correction.
• You will collect and evaluate data on personal experiences, risk assessments, historical complaint data, and production data.
• In addition you will design and develop an ML model that can generate suggestions for actions and assign relevance to predictions as well as train the ML model using historical data and validate its accuracy and effectiveness in supporting quality engineers.
• Moreover, you will implement the ML model in a real-world setting within the organization.
• You will conduct testing to evaluate the model's performance in generating actionable suggestions and its ability to support quality engineers in decision-making.
• Further to this, you will assess the impact of the ML model on the efficiency and effectiveness of the quality management process.
• Last but not least, you will gather feedback from quality engineers and other stakeholders to identify areas for improvement and optimize the ML model based on feedback and performance metrics to enhance its support for the quality management process.

• Education: Master studies in the field of Industrial Engineering, Mechanical Engineering, Computer Science, Data Science, Applied Mathematics, Statistics or comparable
• Experience and Knowledge: proficiency in programming languages such as SQL, Python; strong background in AI, Machine Learning
• Personality and Working Practice: you are a self-starter who works effectively both independently and as part of a team; you identify challenges proactively, propose innovative solutions and have a structured, organized approach to research, combined with excellent analytical and critical thinking skills
• Languages: very good in English or German

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?
Felipe Bolanos (Functional Department)
+49 711 811 12655 
Andreas Alber (Functional Department)
+49 711 811 30098

#LI-DNI