You will conduct independent research while collaborating with a creative team, focusing on practical applications of your studies and having the opportunity to publish your findings.
Anforderungen
- •Good knowledge in machine learning
- •Good knowledge in computer vision
- •Experience in programming with Python
- •Familiarity with PyTorch, NumPy, Pandas
- •Experience in software engineering
- •Writing clean, maintainable code
- •Interest in self-responsible scientific research
- •Studying current ML methods
- •Ability to work independently
- •Ability to work in teams
- •Good language skills in English
- •Good communication skills
- •Ability to be on-site approx. once per week
- •Prior knowledge in anomaly detection is a plus
- •Prior knowledge in domain generalization is a plus
- •Prior knowledge in data-efficient learning is a plus
- •Prior knowledge in uncertainty estimation is a plus
- •Prior knowledge in 3D vision is a plus
- •Especially suitable for students in computer science
- •Especially suitable for students in mathematics
- •Especially suitable for students in engineering
- •Especially suitable for students in similar areas
Deine Aufgaben
- •Work independently and implement your ideas.
- •Publish your research findings.
- •Collaborate with a dynamic and innovative team.
- •Ensure practical relevance to your studies.
Deine Vorteile
Independent work and freedom
Possibility to publish work
Dynamic and innovative team
Practical relevance to studies
Friendly environment and flexible hours
Original Beschreibung
City:
München
Date:
Aug 1, 2025
# Master thesis in AI-based visual quality inspection
**What you will do**
Machine learning techniques show promising results in visual quality inspection reducing the amount of tedious and error-prone manual work. The driving factor is the availability of large amounts of data. However, in this domain data is often sparse or labelling data is expensive. This requires approaches specifically tailored for these low-data applications that are reliable and robust against noise. Master thesis topics are available in the areas of anomaly detection, domain generalization, data-efficient learning, uncertainty estimation, 3D vision.
**What you bring to the table**
* Good knowledge in machine learning and computer vision
* Experience in programming with Python and familiarity with PyTorch, NumPy, Pandas and similar libraries
* Experience in software engineering and writing clean, maintainable code
* Interest in self-responsible scientific research and studying current ML methods
* Ability to work independently and in teams
* Good language skills in English
* Good communication skills
* Ability to be on-site approx. once per week.
Prior knowledge in one or more of these fields is a plus: anomaly detection, domain generalization, data-efficient learning, uncertainty estimation, 3D vision.
**Especially suitable for students with the field of study in computer science, mathematics, engineering, or similar areas.**
**What you can expect**
* Independent work and freedom to implement own ideas
* The possibility to publish your work
* Participation in a dynamic and innovative team
* Practical relevance to your studies
* Friendly working environment and flexible working hours.
We value and promote the diversity of our employees' skills and therefore welcome all applications - regardless of age, gender, nationality, ethnic and social origin, religion, ideology, disability, sexual orientation and identity. Severely disabled persons are given preference in the event of equal suitability.
**Job Segment:**
Inspection, Quality Control Inspector, Research Scientist, Software Engineer, Computer Science, Engineering, Quality, Technology, Science