Internship - EEG & fNIRS Data Acquisition and (Pre-)Processing
ZEISS GroupKarlsruhe, Baden-Württemberg, Germany
Posted March 12, 2025
Internship
About the Company
ZEISS is an internationally leading technology enterprise operating in the fields of optics and optoelectronics. In the previous fiscal year, the ZEISS Group generated annual revenue around 11 billion euros in its four segments Semiconductor Manufacturing Technology, Industrial Quality & Research, Medical Technology and Consumer Markets (30 September 2024). With over 46,000 employees, ZEISS is active globally in around 50 countries with more than 60 sales and service locations, around 40 research and development facilities, and 35 production facilities worldwide (30 September 2024). Founded in 1846 in Jena, the company is headquartered in Oberkochen, Germany. The Carl Zeiss Foundation, one of the largest foundations in Germany committed to the promotion of science, is the sole owner of the holding company, Carl Zeiss AG. Data privacy: www.zeiss.com/data-protection Imprint: http://zeiss.com/publisher This is ZEISS's official LinkedIn account. It follows the ZEISS Netiquette: www.zeiss.com/netiquette
Job Description
We are looking for highly motivated students to support the acquisition, quality control, and curation of EEG and fNIRS data. This role offers a unique opportunity to work hands-on with human neuroimaging data, ensuring high-quality recordings and organizing datasets for research in neural decoding and AI-driven analysis.
Requirements
- Enrolled in a Bachelor's or Master's program in biomedical engineering, electrical engineering, neuroscience, computer science, AI, or related fields
- Strong programming skills in Python and NumPy
- Solid understanding of electrical engineering principles
- Fundamental knowledge of electrophysiology, neural signal processing, and machine learning
- Experience with data preprocessing, signal analysis, and feature extraction is highly desirable
- Familiarity with AI/ML concepts (e.g., supervised/unsupervised learning, deep learning architectures) is a plus
- Creative, pragmatic, and self-motivated with strong analytical skills
- Capable of working independently as well as in a team-oriented environment
- Excellent communication skills in English or German
- Passion for innovation and enthusiasm for new technologies as well as motivation to work in agile, interdisciplinary teams
Benefits
- A dynamic and interdisciplinary research environment
- Hands-on experience with EEG and fNIRS data acquisition and lab equipment
- Exposure to state-of-the-art methods in neural signal processing and data curation
- Opportunity to contribute to AI-ready datasets for machine learning applications for neural decoding
- Close mentorship
- An agile work environment
- The possibility of continuing as part of a Master's thesis project