Internship on Deep Learning Methods for Real-time Object Tracking

Step out of your comfort zone, excel and redefine the limits of what is possible. That's just what our employees are doing every single day – in order to set the pace through our innovations and enable outstanding achievements. After all, behind every successful company are many great fascinating people.

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 high-precision object tracking involving subtasks seeking as pose estimation, semantic segmentation and so on leveraging deep-learning methods from computer vision. Familiarize with the state-of-the-art in pose estimation and tracking applications

Development of the hardware experimental setup based on the use-case

Implementation of prototype solutions relying on methods from both geometric and/or deep learning methods in computer vision

Validation of the results with test measurements

Evaluation of the technical feasibility

Documentation of the experimental outcomes

A background in the STEM area (computer science, robotics engineering, electrical engineering)

Currently enrolled in a master's degree program at a top university

Prior experience with at least one programming language search as C++ or Python

Good theoretical background in linear algebra, optimization, and computer vision methodologie

Demonstrable experience applied with the computer vision (such as OpenCV, PCL, Open3D) and deep learning libraries (Tensorflow/ Pytorch) will be beneficial

Self-motivated and independent working style along with a curiosity for diving into challenging topics that push the state-of-the-art

As a student, you will work on equal footing with your colleagues, you will gain deep insights into a company that creates products for the world of tomorrow, and you will create ideal conditions for your later career.

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