Master Thesis - Discover Optimization Patterns for Next-Generation Automotive Software (f/m/d)

CARIAD; Mönsheim; Hybrid; EUR 40.000 - 60.000; Vollzeit

Zusammenfassung

CARIAD, the automotive software company of the Volkswagen Group, offers a Master Thesis opportunity in analyzing automotive software. The position involves parsing C code, applying traditional and machine learning analysis techniques, and collaborating on improvements for code organization in a remote-friendly environment.

Leistungen

Remote work options within Germany

35-hour week

Qualifikationen

• Enrolled student in Computer Science or a related field.
• Proficiency in C programming and familiarity with software architecture.
• Ideally experience with parsing tools and knowledge of graph representations.

Aufgaben

• Study and apply software pattern analysis techniques.
• Parse real-world automotive C code for structural representation extraction.
• Collaborate with engineers for feedback and validation.

Kenntnisse

C programming

Machine learning

Graph theory

Communication

Ausbildung

Enrolled in Computer Science or comparable

Tools

Python LibClang

NetworkX

PyGraphviz

scikit-learn

Jobbeschreibung

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Client:

CARIAD

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Other

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EU work permit required:

Yes

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Job Reference:

c14928c2bb8c

Job Views:

3

Posted:

27.06.2025

Expiry Date:

11.08.2025

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Job Description:

We are CARIAD, the automotive software company of the Volkswagen Group. Our teams build automotive software platforms and digital customer functions for iconic brands like Audi, Volkswagen, and Porsche - supporting the Volkswagen Group in becoming the leading automotive technology company. With CARIDIANS in Germany, the USA, China, Estonia, and India, we are transforming automotive mobility for everyone.

Join us and be part of this exciting journey!

YOUR TEAM
Our "Vehicle Motion" team is excited to offer a Master Thesis opportunity focused on analyzing real-world automotive software using advanced code analysis techniques. This is your chance to go beyond the surface - by parsing C code, extracting intermediate representations like ASTs, control-flow and data-flow graphs, and applying graph algorithms and possibly machine learning to uncover meaningful code patterns.

Research question: What are the traditional and state-of-the-art static code analysis techniques, and how effectively can they identify and analyze code patterns in complex and entangled automotive application software?

WHAT YOU WILL DO

• Study academic and industrial research on how software patterns are identified and analyzed
• Parse real-world automotive C code to extract structural representations, e.g. graphs
• Create visual or data models (e.g. control-flow or data-flow graphs) to better understand code structure and behavior
• Apply and compare analysis techniques - from traditional algorithms to modern machine learning approaches
• Benchmark the effectiveness of different methods in detecting patterns or anomalies in automotive software
• Summarize findings and suggest improvements for how code can be better organized, maintained or understood
• Collaborate with engineers or researchers for feedback, validation and industry insights
• Present the results and framework in a scientific paper

WHO YOU ARE

• Enrolled student in the field of Computer Science or comparable
• Proficiency in C programming and familiarity with software architecture and code structure
• Team-oriented, growth-minded, goal-focused, and communicative
• Ideally experience with parsing tools (e.g., Python LibClang, or similar)
• Knowledge of graph theory and working with code representations (e.g. ASTs, control-flow, or data-flow graphs) is a plus
• Interest in automotive software development and embedded systems
• Exposure to Python, especially libraries for graph processing (e.g., NetworkX, PyGraphviz) or basic machine learning (e.g., scikit-learn) is a plus

NICE TO KNOW

• Remote work optionswithin Germany
• Duration: 6 months
• 35-hour week

At CARIAD, we embrace individuality and diversity because we believe our differences make us stronger. We actively seek to build teams with a variety of backgrounds, perspectives, and experiences. Our goal is to create an environment where everyone feels valued and empowered to contribute. If you need assistance with your application due to a disability, please reach out to us at [emailprotected] - we are happy to support you.