Master Thesis - Metric-Guided Diffusion Models for High-Fidelity In-Cabin Synthetic Data Genera[...]

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Master Thesis - Metric‑Guided Diffusion Models for High‑Fidelity In‑Cabin Synthetic Data Generation - REF5866V

4 days ago – Be among the first 25 applicants

Company Description

Since its spin‑off in September 2025, AUMOVIO continues the business of the former Continental Group sector Automotive as an independent company. The technology and electronics company offers a wide‑ranging portfolio that makes mobility safe, exciting, connected, and autonomous. This includes sensor solutions, displays, braking and comfort systems as well as comprehensive expertise in software, architecture platforms, and assistance systems for software‑defined vehicles. In the fiscal year 2024 the business areas, which now belong to AUMOVIO, generated sales of 19.6 billion Euro. The company is headquartered in Frankfurt, Germany and has about 87 000 employees in more than 100 locations worldwide.

Job Description

Are you looking for an exciting master’s thesis at the intersection of Generative AI, Computer Vision, and Automotive AI? Would you like to work with state‑of‑the‑art diffusion models while contributing to privacy‑safe, next‑generation driver monitoring systems? Then this thesis could be the perfect fit for you.

We are offering a 6‑month master’s thesis in our AI laboratory in Berlin, with a preferred start date of February 2026.

Your Thesis Tasks

Implement and experiment with diffusion‑based image generation models
Develop an evaluation pipeline for a large‑scale, high‑fidelity synthetic in‑cabin image dataset
Investigate metric‑driven feedback loops to improve image generation quality
Analyze the impact of synthetic data on downstream computer vision tasks
Summarize findings in a master’s thesis and potentially a research paper or patent submission

Qualifications

Enrolled in a master’s program in Artificial Intelligence, Machine Learning, Computer Vision, Computer Science, Robotics, Mathematics, or a related field
Strong Python programming skills
Solid understanding of deep learning and computer vision fundamentals
Experience with PyTorch or similar deep learning frameworks

Nice‑to‑Have Skills

Prior exposure to diffusion models, GANs, or synthetic data generation
Experience with pose estimation, activity recognition, or multimodal models
Familiarity with CLIP, ControlNet, or image quality evaluation metrics
Experience using Git, Docker, and GPU‑based training
Previous research projects, internships, or open‑source contributions are a plus

Personal Skills

Independent, structured, and goal‑oriented
Strong analytical thinkers with good problem‑solving skills
Curious and creative when exploring new ideas
Good communicators who enjoy working in a team
Motivated to deliver high‑quality and reproducible research

Application Requirements

Proof of enrollment in a master’s program
A current transcript of grades
An excerpt from your study regulations confirming master’s thesis requirements

If you are not from the EU, a valid residence permit and work permit (including the additional sheet) are required.

Applications from severely handicapped candidates are explicitly welcome.

Benefits

Close supervision by experienced researchers and PhD students
Access to powerful GPU infrastructure
Flexible working hours with hybrid work options
Participation in journal clubs, technical talks, and networking events
Fair remuneration for your thesis work

We are committed to diversity, inclusion, and belonging. We offer equal opportunities to everyone – regardless of age, gender, nationality, cultural background, disability, religion, ideology or sexual orientation.

Ready to take your career to the next level? The future of mobility isn’t just anyone’s job. Make it yours! Join AUMOVIO. Own What’s Next.