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DENSO • Eching, Bavaria, Germany
Role & seniority: Working Student or Master Thesis student (m/f/d) in Systems Engineering R&D; internship/traineeship track, part-time with potential extension.
Stack/tools: Python; machine learning frameworks (e.g., PyTorch) familiarity a plus; diffusion models for traffic scenario/video generation; optimization techniques; integration into existing testing workflow.
Adapt diffusion models to generate traffic scenarios and traffic videos.
Develop criticality metrics and optimization-based methods to steer generation toward critical scenarios.
Integrate methods into the existing testing workflow and evaluate test campaigns to extract key test cases.
Pursuing B.Sc/M.Sc in Computer Science, Electrical Engineering, or related field.
Strong Python programming skills.
English or German fluent; ability to work independently and in a team.
Experience with PyTorch or similar ML training frameworks.
Familiarity with optimization, dynamical systems, or control engineering.
Location & work type: Not specified; project runs 6 months with potential extension; located within an international company environment (DENSO). Roles available as internship/praktikum or master thesis; likely candidate to align with European/Global offices.
Company Description
As an automotive supplier, DENSO is leading in developing and providing components and systems for heating, air conditioning, motor cooling, exhaust gas aftertreatment, automotive electrics and electronics and instrumentation.
Job Description
Complexity and scale of automotive systems are increasing, particularly in the area of automated driving and advanced driving assistance systems. The increased complexity of such safety-critical systems demands for advanced testing and verification methods to ensure safety under an abundance of operating conditions and traffic scenarios that may be encountered.
Recently, generative AI has shown promising results for content generation, such as for text (ChatGPT), image (stable diffusion), or video generation (OpenAI SORA). In our R&D work, we would like to explore the possibilities of using generative AI to create critical traffic scenarios learned from traffic data.
We are seeking for a talented and driven Working Student / Master thesis student (m/f/d) to join the Systems Engineering R&D team and support the development of testing methods by using recent results from generative AI for scenario and traffic video generation. In your role, you gain hands-on experience on the training and validation of generative AI models, and contribute to our R&D testing platform for automated driving. The work is part of the public funded project nxtaim.de.
Responsibilities
Adaptation of a diffusion model for traffic scenario/video generation Develop criticality metrics for traffic scenarios Develop optimization-based techniques to guide the generation towards critical scenarios Integration of the methods into our existing testing workflow Evaluate the testing campaign to extract critical test case
Qualifications
Pursuing a B.Sc/M.Sc degree in Computer Science, Electrical Engineering, or a related field. Strong programming skills in Python. Familiarity with machine learning training frameworks (e.g. pytorch) is a big plus. Familiarity with optimization / dynamical systems / control engineering is a plus. Fluent level of English or German is required. Team player with intercultural competencies as well as independent working style with good self-organization capabilities.
Additional Information
The project will first run for 6 months, with the possibility of extension.
Employee-Benefits: Urban Sports Club etc.
Attractive working environment: Modern offices, own canteen, free parking spaces
International company: Career opportunities in a global environment
Open company culture: Diverse, multicultural team
Events: Regular company & team events
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By making you aware of this, we hope to avoid and ultimately stop victims from falling for this scam. Please do not provide any personal or financial information and do not send any money to anyone you suspect of recruitment fraud.
If you are contacted by someone whom you suspect may not be appropriately representing DENSO, please email: [email protected]. Please forward the original email that you received that includes the original subject line and complete header information.
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Karrierestufe Ausbildung/Praktikum Beschäftigungsverhältnis Praktikum Tätigkeitsbereich
Wissenschaft und Bildung und Trainee/Praktikant: in Branchen Automobil