Students: Artificial Intelligence in Semiconductor Technology

The particular strength of the Fraunhofer Institute for Electronic Nano Systems ENAS lies in the development of smart systems for various applications. The systems combine electronic components, micro and nano sensors, and actuators with interfaces for communication. Fraunhofer ENAS develops individual components, the technologies for their production, as well as system concepts and system integration technologies and transfers them into practical use. Fraunhofer ENAS accompanies customer projects from the idea to the design, technology development, or implementation using existing technologies right through to the tested prototype.

The Data-based Methods team at Fraunhofer ENAS develops real-world applications using AI, machine learning, and computer vision. The main focus is on semiconductor manufacturing and medical technology.

Are you passionate about cutting-edge research at the intersection of semiconductor technology and artificial intelligence? Join us as a student in our team for artificial intelligence and data based methods at the Fraunhofer Institute of Electronic Nanosystems (ENAS).

We're on a mission to create digital twins for highly complex semiconductor manufacturing processes - enabling process optimization and model-based control. As the industry moves towards more individualized processes and products, a significant challenge is to enable accurate predictions with limited reference data. Therefore, we employ a broad range of artificial intelligence algorithms that enrich process data with sophisticated domain knowledge and semi-supervised approaches to incorporate unlabeled data.

We are currently looking for students for Master's theses, internships and student assistants. We can discuss our ideas together to find the right job for you. What you contribute

You already have some practical experience with AI and Machine Learning algorithms. Excellent programming skills (preferably with Python) are required. A strong interest in interd