Master thesis in AI-based visual quality inspection

Fraunhofer-Gesellschaft; Deutschland; Hybrid; EUR 40.000 - 60.000; Vollzeit

Zusammenfassung

A leading research institute in Germany is offering master thesis topics in machine learning focused on low-data applications such as anomaly detection and 3D vision. We're looking for students in computer science or related fields who have strong knowledge in machine learning, experience in programming with Python, and are eager to contribute to innovative research. The role allows for independent work with flexible hours, fostering a supportive team environment.

Leistungen

Independent work

Possibility to publish work

Flexible working hours

Friendly working environment

Qualifikationen

• Good knowledge in machine learning and computer vision.
• Experience in programming with Python and libraries like PyTorch, NumPy, Pandas.
• Interest in scientific research and current ML methods.

Aufgaben

• Develop machine learning techniques for visual quality inspection.
• Work on topics like anomaly detection and data-efficient learning.
• Conduct independent research and implement own ideas.

Kenntnisse

Machine learning

Computer vision

Python programming

PyTorch

NumPy

Pandas

Software engineering

Independent work

Good communication

Ausbildung

Field of study in computer science, mathematics, engineering, or similar

Jobbeschreibung

Safe Intelligence - this forms the core brand of the Fraunhofer Institute for Cognitive Systems IKS. Connected cognitive systems drive innovation in many sectors, including mobility, healthcare, and automation in industry. Disruptive technologies such as artificial intelligence and quantum computing play a key role here. Fraunhofer IKS is conducting research to ensure that these applications are reliable and verifiably safe. We consider resilience and intelligence to be part of the same process.

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.

With its focus on developing key technologies that are vital for the future and enabling the commercial utilization of this work by business and industry, Fraunhofer plays a central role in the innovation process. As a pioneer and catalyst for groundbreaking developments and scientific excellence, Fraunhofer helps shape society now and in the future.

Interested? Apply online now with your motivation letter, cv and a current transcript of records. We look forward to getting to know you!

Please address your application to Lena Heidemann.

If you got questions, please contact our colleagues from HR via eMail: [e-mail] (this email-address is only for questions, we don't accept any applications via our email-address)

Fraunhofer Institute for Cognitive Systems IKS

www.iks.fraunhofer.de

Requisition Number: 80771 Application Deadline: