Internship/ Master Thesis on Foundation Models for Object Tracking (f/m/x)

As a student worker, you will work side by side with your coworkers as equals in an environment which will allow you create the ideal con- ditions for your future career. 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 silence 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.

We are seeking passionate and talented students who are eager to shape next-generation products at ZEISS. Integrated within a team of scientists and engineers, you will work on research topics in 3D computer vision and robotics. The project is based on developing robust object tracking algorithms leveraging recent development of vision foundation models.

With us, you have the opportunity to perfectly combine your practical studies while participating in exciting projects. This allows you to gain valuable skills, expand your network, and grow both professionally and personally. Literature Review: Familiarize yourself with the state-of-the-art in object tracking and vision models

Prototype Development: Implement prototype solutions using state-of-the-art techniques in object tracking

Experimental Validation: Validate your results through measurements conducted in a laboratory setup

Technical Evaluation: Assess the technical success of your solutions

Documentation: Thoroughly document experimental outcomes and test results for future reference analysis

Currently enrolled in a Master's degree in a STEM field (Computer Science, Robotics Engineering, Electrical Engineering)

Proficiency in Python is mandatory; prior programming experience is essential

Strong foundation in linear algebra, optimization, and methodologies in computer vision

Demonstrable experience in utilizing vision foundation models is a plus

A self-motivated and independent working style, coupled with a strong curiosity for tackling challenging topics that advance the state-of-the-art

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

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