Internship – Physical AI for Surgical Robotics (f/m/x)

Motivation for 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.

Your Role

Integrated into a team of scientists and research engineers, you will work on research projects in surgical robotics.

• Development and testing of concepts for physical AI in surgery

• Exploring how modern AI and computer vision techniques can be employed for surgical scene understanding, synthetic data generation, and robotic automation for surgical tasks

• Conducting hands-on lab work with phantom or ex-vivo animal models

• Presenting and discussing research findings in team and department meetings

• Working with researchers and engineers in a collaborative environment at the ZEISS Innovation Hub Karlsruhe, located at the KIT Campus North

What We Offer

• An opportunity to build the foundation for next-generation products in computer-assisted surgery & surgical robotics

• A dynamic and international team with an active student community

• Hands-on research experience in surgical scene understanding, including experimental lab work

• Mentorship by experienced PhD-level experts

• A modern working environment with state-of-the-art tools for research (AI-assisted coding, etc.)

Your Profile

• Enrolled in a bachelor's or master's degree program in computer science, robotics, engineering, or a related field

• A solid foundation in deep learning and AI (e.g., semantic segmentation, information fusion, trajectory planning), with practical programming experience in Python and deep learning frameworks such as PyTorch, or the NVIDIA Omniverse Frameworks

• Interested in developing innovative solutions for computer-assisted surgery

• An open-minded attitude, a hands-on approach and enthusiasm for working in agile, interdisciplinary teams

• Strong communication skills in English and/or German

• Idealyy gained experience in one or more of the following areas: foundation models, world models, Reinforcement Learning, Gaussian Splatting, multi-modal data fusion, or OCT imaging

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: