The particular strength of the Fraunhofer Institute for Electronic Nano Systems ENAS lies in the development of smart systems - so-called intelligent 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.
Do you have a passion for developing application-oriented computer vision pipelines for semiconductor metrology? Join our team as a student and contribute to the development of computer vision models for analyzing measurements on metrology equipments. Our goal is to increase the efficiency of semiconductor manufacturing by automating image analysis, utilizing web-based user interfaces and simplifying reporting.
Key responsibilities:
* Development of computer vision models to analyze measurement data.
* Extract meaningful information from metrological data.
* Deploy your pipeline in web-based user interfaces.
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 bring to the table
* Strong understanding and practical experience with image processing methods or computer vision models.
* Excellent programming skills (preferably in Python) are required.
* Strong abstract and mathematical thinking skills.
* A strong interest in interdisciplinary work at the interface of software engineering, data science and semiconductor metrology is essential.
* Still studying in Chemnitz, Mittweida or the surrounding area.
* An average grade
Requisition Number: 73238 Application Deadline: 12/31/2024