ZEISS
Internship–DeepLearningforVideoUnderstanding(m/f/x)
Neural analysis suggests this role is
optimal for Entry candidates.
“Internship – Deep Learning for Video Understanding (m/f/x) at ZEISS. Skills: Deep Learning, Video Understanding, Python, ML Frameworks. Contribute to research. Develop models”
Industry & Context.
independent on open-ended problems
What They're Looking For.
Must Have
Master’s in Computer Science, Machine Learning, Python, ML frameworks
Nice to Have
video analysis, multimodal learning, foundation models
What You'll Do.
Contribute to research, Develop models, evaluate models, Work with datasets, Implement approaches, extend approaches
How You'll Work.
Communication Scope
communication; presentation skills
Full Job Description
# **Your Role** 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 # **Your Profile** * 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.). Your ZEISS Recruiting Team: Franziska Gansloser
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