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 state-of-the-art machine learning methods Develop and evaluate models for anomaly detection in multi-variate time series (e.g.time-series foundation models, video-language models, latent diffusion or LLMs) Work with real-world datasets and problem settings from ZEISS applications Implement and analyze state-of-the-art approaches and extend them in a Zeiss 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 multi-variate time series, Vision language models, anomaly detection or foundation models is a plus 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