Internship – Deep Learning for Video Understanding (m/f/x)

As a student, you work with your colleagues on an equal footing and create ideal conditions for your future career.

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 regardless 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.

With us, you have the opportunity to perfectly combine your studies with practical experience while actively contributing to exciting projects. This allows you to gain valuable skills, expand your network, and grow both professionally and personally.

• Contribute to research on video-based machine learning methods

• Develop and evaluate models for semantic video understanding (e.g., Object interaction in video, dynamic scene understanding, semantic segmentation)

• Work with real-world datasets and problem settings from ZEISS applications

• Implement and analyze state-of-the-art approaches and extend them in a research-driven setting

• Enrolled in a Master's in Computer Science, Machine Learning, or a related field

• Strong fundamentals in machine learning and deep learning

• Experience with Python and common ML frameworks (e.g. PyTorch)

• Interest in research and ability to work independently on open-ended problems

• Experience with video analysis, multimodal learning, or foundation models is a plus

• High motivation, creativity, flexibility, and a structured and independent way of working effective communication and presentation skills

Sounds exciting? Then become part of #teamZEISS and help us shape the future! Please provide your complete application documents (CV, transcript of records, etc.).