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 such as pose estimation, semantic segmentation and so on leveraging deep-learning methods from computer vision. Your role 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 & test results As a student, you will work on an 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. Your profile 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 such as C++ or Python Good theoretical background in linear algebra, optimization, and computer vision methodologies Experience with CAD modelling software for 3D printing prototype objects will be beneficial Demonstrable applied experience 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 Your ZEISS Recruiting Team: Franziska Gansloser