Internship - EEG & fNIRS Data Acquisition and (Pre-)Processing

Step out of your comfort zone, excel and redefine the limits of what is possible. That's just what our employees are doing every single day – in order to set the pace through our innovations and enable outstanding achievements. After all, behind every successful company are many great fascinating people.

In a spacious modern setting full of opportunities for further development, ZEISS employees work in a place where expert knowledge and team spirit reign supreme. All of this is supported by a special ownership structure and the long-term goal of the Carl Zeiss Foundation: to bring science and society into the future together.

Join us today. Inspire people tomorrow.

Diversity is a part of ZEISS. We look forward to receiving your application silence of gender, nationality, ethnic and social origin, religion, philosophy of life, disability, age, sexual orientation or identity.

Apply now! It takes less than 10 minutes.

Motivation of the Work Turning today's research into tomorrow's applications – together. At ZEISS, we focus on user-centric innovation to transform ideas into cutting-edge solutions. The ZEISS Innovation Hub @ KIT fosters collaboration between students, researchers and industry professionals to drive technological advancements in neuroscience applications. We are looking for highly motivated students to support the acquisition, quality control, and curation of EEG (Electroencephalography) and fNIRS (functional Near-Infrared Spectroscopy) 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. If you are passionate about neuroscience, and signal processing and eager to contribute to cutting-edge research, join us!

We offer 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

Your Role Develop an efficient and reproducible workflow for EEG and fNIRS data acquisition and preprocessing Implement quantitative metrics to assess and optimize data quality

Curate and organize large datasets of stimulus-brain activity pairs for research applications

Establish online and offline methods for detecting and flagging bad recordings using visualization tools

Apply and measured advanced preprocessing techniques to increase the signal-to-noise ratio

Prepare data pipeline for AI and machine learning models (feature extraction, artifact removal, and normalization)

Collaborate with a team of engineers, neuroscientists, and AI researchers to integrate deep learning approaches into neural decoding

Present and discuss research findings in team and department meetings

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 pre dataprocessing, 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 German

Passion for innovation and enthusiasm for new technologies as well as motivation to work in agile, interdisciplinary teams

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