We are seeking passionate and talented students who wants to make an impact by shaping next-generation products at ZEISS. Together with a team of students, scientists and research engineers, you will design, implement, and evaluate cutting-edge deep learning methodologies for the integration and fusion of foundation models for monocular depth estimation and disparity networks. By adapting these methods to support real-world problems you will help to build the foundation for next-generation visualization technologies.
What We Offer
The possibility to learn and implement cutting edge technology
Interpersonal and interdisciplinary mentorship by experienced PhD-level experts
A modern working environment enabling hybrid work by offering remote workdays
An opportunity to join a growing company with many career options
Currently enrolled in a bachelor’s or master's degree in computer science, mathematics, physics or related fields
Very good coding experience, preferably Python
Interested in technology and motivated to cooperate on demanding tasks
Enthusiastic to learn and explore with a high degree of initiative and creativity
Committed to collaborating in cross-functional teams
Good communication skills in English, German is a plus
Your ZEISS Recruiting Team:
Falk Dymke
