Thesis Internship – Advanced Data Analytics for Functional Safety Validation

About the role

You will join Bosch's Application team in Turin, working on advanced engine control systems in a dynamic automotive environment. Supported by experienced engineers, you will apply data analytics to real vehicle development projects and contribute to functional safety validation.

Key responsibilities

• Define a methodology to structure and label data‑analysis results from vehicle validation, ensuring traceability to functional safety requirements.
• Perform root‑cause analysis of availability and robustness issues identified during vehicle testing.
• Develop KPI‑based metrics and data‑driven validation criteria (e.g., adaptive thresholds, signal envelopes) to assess safety performance.
• Build a decision framework that automatically classifies safety requirements (validated / not validated / uncertain) from measurement data.
• Analyze large datasets with machine‑learning techniques to uncover hidden patterns and safety‑relevant scenarios.
• Design a scalable data‑storage concept to enable reuse of analysis results and support statistical monitoring.

Required profile

• Current enrolment in a Master’s or PhD program in Computer Science, Electrical Engineering, Data Science or a related field.
• Strong interest in automotive systems and functional safety (ISO 26262).
• Ability to work independently and collaboratively in a multidisciplinary team.
• Good written and spoken English communication skills.

Required skills

• Machine learning techniques for data analysis.
• Data analysis and statistical methods.
• Understanding of functional safety concepts (ISO 26262).

What we offer

• Hands‑on experience with real vehicle and test‑bench measurement data.
• Mentoring by senior engineers and exposure to Bosch’s automotive development processes.
• Opportunity to publish a thesis based on a real‑world industrial project.